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  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "### **CLIP-E Crossentropy**\n",
        "\n",
        "This notebook contains the CLIP-E crossentropy model inference for visual sentiment classification using the labels of Parrot model. The model was trained using the WEBemo dataset. We test the three problem configuration: binary, 6 categories and 25 categories"
      ],
      "metadata": {
        "id": "HOLfnrnz3wDe"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 1. First, download model weights, test images and dependency libraries"
      ],
      "metadata": {
        "id": "FLXOZJcp5WsQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install transformers"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tN3h5Rhxorvt",
        "outputId": "34d81018-9bb0-44b5-a9b4-f58f576c28d4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting transformers\n",
            "  Downloading transformers-4.33.3-py3-none-any.whl (7.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m31.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.12.2)\n",
            "Collecting huggingface-hub<1.0,>=0.15.1 (from transformers)\n",
            "  Downloading huggingface_hub-0.17.3-py3-none-any.whl (295 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m295.0/295.0 kB\u001b[0m \u001b[31m40.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.23.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2023.6.3)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.31.0)\n",
            "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1 (from transformers)\n",
            "  Downloading tokenizers-0.13.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m83.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting safetensors>=0.3.1 (from transformers)\n",
            "  Downloading safetensors-0.3.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m81.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.1)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.15.1->transformers) (2023.6.0)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.15.1->transformers) (4.5.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.2.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.4)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2023.7.22)\n",
            "Installing collected packages: tokenizers, safetensors, huggingface-hub, transformers\n",
            "Successfully installed huggingface-hub-0.17.3 safetensors-0.3.3 tokenizers-0.13.3 transformers-4.33.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# images for testing\n",
        "!wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=1F25x62Z625zJl6ZUN0eBLfuFbwoJD0Ev' -O img_test_1.jpg\n",
        "!wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=1aTNaIyqo1lVoFBOIR8GbsXp-0au3s_dX' -O img_test_2.jpg"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/"
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        "id": "ZIjED5-Z03V6",
        "outputId": "bdba4935-49bf-4a2e-d3da-850a219593c2"
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      "execution_count": null,
      "outputs": [
        {
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          "text": [
            "--2023-10-02 21:50:02--  https://docs.google.com/uc?export=download&id=1F25x62Z625zJl6ZUN0eBLfuFbwoJD0Ev\n",
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            "HTTP request sent, awaiting response... 303 See Other\n",
            "Location: https://doc-0g-3s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/t4nhmsrrqqnpjbiohkl374a0tv6qlpns/1696283400000/03683847712226052473/*/1F25x62Z625zJl6ZUN0eBLfuFbwoJD0Ev?e=download&uuid=aa1b7a48-f517-43f7-a329-d7060cbe221a [following]\n",
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            "Resolving doc-0g-3s-docs.googleusercontent.com (doc-0g-3s-docs.googleusercontent.com)... 142.251.31.132, 2a00:1450:4013:c1a::84\n",
            "Connecting to doc-0g-3s-docs.googleusercontent.com (doc-0g-3s-docs.googleusercontent.com)|142.251.31.132|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 17741 (17K) [image/jpeg]\n",
            "Saving to: ‘img_test_1.jpg’\n",
            "\n",
            "img_test_1.jpg      100%[===================>]  17.33K  --.-KB/s    in 0s      \n",
            "\n",
            "2023-10-02 21:50:03 (99.1 MB/s) - ‘img_test_1.jpg’ saved [17741/17741]\n",
            "\n",
            "--2023-10-02 21:50:03--  https://docs.google.com/uc?export=download&id=1aTNaIyqo1lVoFBOIR8GbsXp-0au3s_dX\n",
            "Resolving docs.google.com (docs.google.com)... 74.125.143.100, 74.125.143.101, 74.125.143.138, ...\n",
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            "Warning: wildcards not supported in HTTP.\n",
            "--2023-10-02 21:50:04--  https://doc-0o-3s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/uho1633g54hhjb55vpo37ing9jm8htpv/1696283400000/03683847712226052473/*/1aTNaIyqo1lVoFBOIR8GbsXp-0au3s_dX?e=download&uuid=a0f2db81-3f46-4196-9b45-761fb73344ae\n",
            "Resolving doc-0o-3s-docs.googleusercontent.com (doc-0o-3s-docs.googleusercontent.com)... 142.251.31.132, 2a00:1450:4013:c1a::84\n",
            "Connecting to doc-0o-3s-docs.googleusercontent.com (doc-0o-3s-docs.googleusercontent.com)|142.251.31.132|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 14533 (14K) [image/jpeg]\n",
            "Saving to: ‘img_test_2.jpg’\n",
            "\n",
            "img_test_2.jpg      100%[===================>]  14.19K  --.-KB/s    in 0s      \n",
            "\n",
            "2023-10-02 21:50:04 (82.3 MB/s) - ‘img_test_2.jpg’ saved [14533/14533]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#model weights\n",
        "!wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=1-sCP36biH4-Mtyzt09BiVb6iIeNn9_ZQ' -O clip-e_6cat.hdf5\n",
        "!wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=14P8gqTA_J0g2JBCYItyMyCaKV7ap-Qdr' -O clip-e_25cat.hdf5\n",
        "!wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=1B6gcOuAeUkPW_v8iBsj_AwZ2r19hH4M2' -O clip-e_binary.hdf5"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_wJqoKa-sMfK",
        "outputId": "56e8cf90-c9f7-42a6-b635-ecba25524b4f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2023-10-02 21:10:39--  https://docs.google.com/uc?export=download&id=1-sCP36biH4-Mtyzt09BiVb6iIeNn9_ZQ\n",
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            "Connecting to docs.google.com (docs.google.com)|74.125.143.113|:443... connected.\n",
            "HTTP request sent, awaiting response... 303 See Other\n",
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            "Resolving doc-00-3s-docs.googleusercontent.com (doc-00-3s-docs.googleusercontent.com)... 142.251.31.132, 2a00:1450:4013:c1a::84\n",
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            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 1077792 (1.0M) [application/octet-stream]\n",
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            "\n",
            "--2023-10-02 21:10:40--  https://docs.google.com/uc?export=download&id=14P8gqTA_J0g2JBCYItyMyCaKV7ap-Qdr\n",
            "Resolving docs.google.com (docs.google.com)... 74.125.143.113, 74.125.143.139, 74.125.143.101, ...\n",
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            "Location: https://doc-0k-3s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/4pfsdp9eujhkfatml2srfhuhu8g72qd3/1696281000000/03683847712226052473/*/14P8gqTA_J0g2JBCYItyMyCaKV7ap-Qdr?e=download&uuid=8941c909-817c-401c-b918-ccc33a8203ad [following]\n",
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            "\n",
            "--2023-10-02 21:10:41--  https://docs.google.com/uc?export=download&id=1B6gcOuAeUkPW_v8iBsj_AwZ2r19hH4M2\n",
            "Resolving docs.google.com (docs.google.com)... 74.125.143.113, 74.125.143.139, 74.125.143.101, ...\n",
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            "HTTP request sent, awaiting response... 303 See Other\n",
            "Location: https://doc-0o-3s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/li847hip45ellmq3i2csnoh45en0fl3e/1696281000000/03683847712226052473/*/1B6gcOuAeUkPW_v8iBsj_AwZ2r19hH4M2?e=download&uuid=f1d8f3e4-0684-4849-af43-03c4aa62587e [following]\n",
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            "Length: 1067552 (1.0M) [application/octet-stream]\n",
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            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 2. Imports"
      ],
      "metadata": {
        "id": "a5BO5r5e5zaF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from PIL import Image\n",
        "import tensorflow as tf\n",
        "from transformers import AutoProcessor, AutoTokenizer, TFCLIPModel"
      ],
      "metadata": {
        "id": "uX14KmK8pcfH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 3. CLIP-E Cross-entropy model"
      ],
      "metadata": {
        "id": "0VtdznU-5_YC"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Utilizing the CLIP input space, we fine-tuned the image embeddings to capture sentiment with minimal training. The model was trained on the WEBemo dataset, which image were labeled using the Parrot emotion categories. These labels follow a hierarchical structure, comprising binary emotions, primary emotions (6 categories), and secondary emotions (25 categories).\n",
        "\n",
        "As a result, there are three versions of the model: one for classifying between positive and negative emotions, another for recognizing the 6 primary emotions, and a third for classifying among the 25 most fine grained emotions"
      ],
      "metadata": {
        "id": "Zl2A52KJTHhe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def CLIP_e_crossentropy(num_classes=25, activation='softmax'):\n",
        "    IMG_FEATURES_SIZE = 512\n",
        "    INPUT_img = tf.keras.layers.Input(shape=(IMG_FEATURES_SIZE),name='input_img_features')\n",
        "    fc = tf.keras.layers.Dense(512, activation='relu', name='img_fc1')(INPUT_img)\n",
        "    preds = tf.keras.layers.Dense(num_classes,activation=activation,name='preds')(fc)\n",
        "\n",
        "    model = tf.keras.models.Model(inputs=INPUT_img, outputs=preds)\n",
        "    #model.summary()\n",
        "    return model"
      ],
      "metadata": {
        "id": "2mZrsZsz6ScL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "3.1  Load original trained CLIP from huggingfaces to extract the image embeddings. Then, CLIP-E crossentropy model's input are the image embeddings"
      ],
      "metadata": {
        "id": "SCO-pIjT9rdC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "clip_model_tf =  TFCLIPModel.from_pretrained(\"openai/clip-vit-base-patch32\")\n",
        "processor = AutoProcessor.from_pretrained(\"openai/clip-vit-base-patch32\")\n",
        "tokenizer = AutoTokenizer.from_pretrained(\"openai/clip-vit-base-patch32\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 362,
          "referenced_widgets": [
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        },
        "id": "xpiXWfcghQ5T",
        "outputId": "ba7b325c-2b21-4773-9d02-79c1699926d8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/4.19k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bd0a6a1feb654f3a9dc932beb2fe5aa7"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading tf_model.h5:   0%|          | 0.00/606M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "6efa29d87e2346268032f840fae18b02"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "All model checkpoint layers were used when initializing TFCLIPModel.\n",
            "\n",
            "All the layers of TFCLIPModel were initialized from the model checkpoint at openai/clip-vit-base-patch32.\n",
            "If your task is similar to the task the model of the checkpoint was trained on, you can already use TFCLIPModel for predictions without further training.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)rocessor_config.json:   0%|          | 0.00/316 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "727dbdcd6b8b4f5687a54c1a08ae7018"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/568 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "625c2756a95f4f99ac143ca259fcfe80"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/vocab.json:   0%|          | 0.00/862k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f87cdf2bfb764a31b799335469337733"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "4180991ac52a4cfc8589c664b4e4cf1d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/2.22M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7c1b3786e5a747c8a011ffa97640752d"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/389 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a1b37764a870499eb6b3acffb812e570"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4. Inference"
      ],
      "metadata": {
        "id": "1IdbsnFq-i-g"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4.1 Fine grained model: 25 categories\n",
        "\n"
      ],
      "metadata": {
        "id": "yUtuzXhP-t0z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 25 categories\n",
        "sentiment_labels = ['affection',  'cheerfullness',  'confusion',  'contentment','disappointment', 'disgust','enthrallment','envy',\n",
        "\t        'exasperation','gratitude','horror',  'irritabilty', 'lust','neglect','nervousness','optimism','pride','rage',\n",
        "\t        'relief', 'sadness','shame',  'suffering', 'surprise', 'sympathy', 'zest']"
      ],
      "metadata": {
        "id": "3uxfe0fR_BsS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Visualize the test image"
      ],
      "metadata": {
        "id": "0Exu0WjH_g9s"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "img_name = 'img_test_1.jpg'\n",
        "image = Image.open(img_name)\n",
        "image"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "E0dMTOXbhu77",
        "outputId": "f17bc60f-bfbb-4682-bcdc-1e41cb7df284"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=146x220>"
            ],
            "image/png": 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\n"
          },
          "metadata": {},
          "execution_count": 74
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Extract the embeddings from original CLIP model"
      ],
      "metadata": {
        "id": "z-EK56WdAOT2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# get visual embedding\n",
        "inputs = processor(images=image, return_tensors=\"tf\")\n",
        "image_features = clip_model_tf.get_image_features(**inputs)\n",
        "image_features = image_features.numpy()\n",
        "image_features.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G1zMuuaXiMHA",
        "outputId": "3731c1f6-95a4-4ad9-cd01-da21ff50d81d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1, 512)"
            ]
          },
          "metadata": {},
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Call our trained CLIP-E crossentropy model** 😊😍😭😀😒😡"
      ],
      "metadata": {
        "id": "FrDc0smrBHBT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model = CLIP_e_crossentropy()\n",
        "model.load_weights('clip-e_25cat.hdf5')"
      ],
      "metadata": {
        "id": "jn6My2J-_kF8"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Inference**"
      ],
      "metadata": {
        "id": "6y-IoPVsBxHv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "preds = model.predict(image_features, verbose=0)\n",
        "preds = np.squeeze(preds)\n",
        "y = np.argmax(preds)\n",
        "\n",
        "print('Sentiment Classification:', sentiment_labels[y])\n",
        "image"
      ],
      "metadata": {
        "id": "vDvERMhwCnIg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 254
        },
        "outputId": "b9299316-2586-441e-b0ea-be20a5840829"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sentiment Classification: nervousness\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=146x220>"
            ],
            "image/png": 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\n"
          },
          "metadata": {},
          "execution_count": 77
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "It's also interesting to see the top-k predictions"
      ],
      "metadata": {
        "id": "KTr4COtnEfFN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "k = 5\n",
        "\n",
        "preds_ordered = np.sort(preds)[::-1]\n",
        "preds_ordered_index = np.argsort(preds)[::-1]\n",
        "sentiment_labels_np = np.asarray(sentiment_labels)\n",
        "top_k_preds = sentiment_labels_np[preds_ordered_index]\n",
        "\n",
        "print('Top ', k, ' predictions')\n",
        "for i in range(k):\n",
        "  print(str(i+1)+':',top_k_preds[i])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OlTPyJBiET9x",
        "outputId": "1af4f293-2a49-438c-9a76-50887c63915c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Top  5  predictions\n",
            "1: nervousness\n",
            "2: sadness\n",
            "3: shame\n",
            "4: disappointment\n",
            "5: neglect\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4.2 Primary emotions: 6 categories\n"
      ],
      "metadata": {
        "id": "0t0siNDhRl9M"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sentiment_labels_6_cats = ['anger', 'fear', 'joy','love','sadness','surprise']\n",
        "\n",
        "model_6_cats = CLIP_e_crossentropy(num_classes=6)\n",
        "model_6_cats.load_weights('clip-e_6cat.hdf5')\n",
        "\n",
        "preds = model_6_cats.predict(image_features, verbose=0)\n",
        "preds = np.squeeze(preds)\n",
        "y = np.argmax(preds)\n",
        "print('Sentiment 6 categories Classification:', sentiment_labels_6_cats[y])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "enxVox1IRof3",
        "outputId": "bbef1854-8730-49bc-f0ca-75ee52e3b876"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sentiment 6 categories Classification: sadness\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4.3 Binary emotions: Negative or Positive\n"
      ],
      "metadata": {
        "id": "YlE-gr7wV4P9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "binary_sentiment_labels = ['negative', 'positive']\n",
        "\n",
        "model_binary = CLIP_e_crossentropy(num_classes=1,activation='sigmoid')\n",
        "model_binary.load_weights('clip-e_binary.hdf5')\n",
        "\n",
        "preds = model_binary.predict(image_features, verbose=0)\n",
        "preds = preds[0][0]\n",
        "y = int(preds > 0.5)\n",
        "print('Binary sentiment Classification:', binary_sentiment_labels[y])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "690_Wx5XSGtw",
        "outputId": "04eac737-2a6b-4c43-c6b2-e31b258d5bd5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Binary sentiment Classification: negative\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4.4 Observing the hierarchical predictions"
      ],
      "metadata": {
        "id": "lHABrE17WXZ1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "img_name = 'img_test_2.jpg'\n",
        "image = Image.open(img_name)\n",
        "inputs = processor(images=image, return_tensors=\"tf\")\n",
        "image_features = clip_model_tf.get_image_features(**inputs)\n",
        "image_features = image_features.numpy()\n",
        "\n",
        "#binary preds\n",
        "preds = model_binary.predict(image_features, verbose=0)\n",
        "preds = preds[0][0]\n",
        "y = int(preds > 0.5)\n",
        "print('Binary sentiment Classification:', binary_sentiment_labels[y])\n",
        "\n",
        "# 6 cats\n",
        "preds = model_6_cats.predict(image_features, verbose=0)\n",
        "y = np.argmax(np.squeeze(preds))\n",
        "print('Sentiment 6 categories Classification:', sentiment_labels_6_cats[y])\n",
        "\n",
        "#25 cats\n",
        "preds = model.predict(image_features, verbose=0)\n",
        "y = np.argmax(np.squeeze(preds))\n",
        "print('Sentiment 25 categories Classification:', sentiment_labels[y])\n",
        "\n",
        "image"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 216
        },
        "id": "Myum4BVOWl2A",
        "outputId": "8c92e1b7-fa97-47cd-a7da-726cce1cae68"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Binary sentiment Classification: positive\n",
            "Sentiment 6 categories Classification: joy\n",
            "Sentiment 25 categories Classification: relief\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=220x147>"
            ],
            "image/png": 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hth/+HeE5eOcfniwDuGGZbOebS77v54O0uzDNRsm84Csl8GITYLeJH6ELlgk3s/cCIX140iS6/pqN8nH1nbf+/t1HXOsl37ZLKuyFe3B97rHoA7ZFNxGjGBE5R2JF/mYzQ+dOzk5/65/+xunjB3uT8eL85Ojg8DOf/dRLdw5Sklf/0p/7+KsvvPnW/ffefevHfvJzQzImYCZCyGIpJe89E145O7FLl8+Hin5I7mg3eEZ+VG3XkWM3j/ZG8b0rmndJ8woke0G5u7j3jvv1GX10I1V3iHVXON5kctw42zfM4dYwst3L8JLb82bvyI3fb8k6MC67GHzlCGIE0VTXngHOVsvf+fJv/s5v/9b5k4cv3rv7Mz/x45NR1Z6f/85v/YZjP93b/9wnXwHU0ExFVC2jsuraHPTeI6IoiAjSbrT0B+MJm4Q2z0zPh6PSD6TmH1IVuGJlb/g0wnXb7BqifPbA6C5prg2LZwKCZEd73LWIBa8EBKz34rO60SX0/Jl2E25XiOzZOb1WTJsZ7tgQO1r2ZW59HQJwNRwEgJnNIGZQ1VHtzez9999LedCue/Lg/Vv7ex9/5dW9vT3n6Ovf/IZnN5vNvvKVr6y6frx3uOjjg6dP//R/589UjrPBMETnXHCUFXLO3rsSD7prPn9UgWs32Wg7737lHeFDUOeHbHJlvbbq+MWDAG5g/OvI84tLNxdd0iMvc0fYsMMr67S9ZVf00zOrvpGqAM/0ADdPyvMNkQ/fLijyZkB09/trOY2ZdTH6KiCACISK+i6++cZ3v/edb7fL05PHJ3ePDm8dHH71d3/v7/3tv/MLv/wL88XZC/c+9u3X3njrrbe++c1vkqv8ePz+w1MV/GN/4o9Pxo33Puesbo0TEV6IGrtxnz7nHS8GrTfM5x8mQHJpqvFCY96lyN1xfoD1fQn52x6a3rngIh5ih5ovh+xvdIjr9JUfXonZfZlLXd0ACT3bw7U6+EVX1+0oAPCB0SDmFLwHgAcP33v6+OGto4Pz3P3+m29877vf/62nJ3Vdz1fLp3/n71ZV9fTxP7l1dHD3+PbnP/eT33n9e5PR3j/9J78xX7S379758R//8XEdcgZVYEYRzPKHZzj/ARnpz9XdP+BefCetT7VdCqJ+rkFw6WjEzi2712x726ZVga3WaIC4zu94Kd5iPWL5QDK9bNBcH4nxozpje2O8Y8517buUHIIsV3/jr/3np6dPT+dnB+NRjPHrX//662+8tVyu5vP54cGtL3zhC3/hL/2Zup782j/89b/z9/5B3Yyn06mvXN/3P/5TP/+//Q//d824TjkykiOnBsoANx0U/xE1tOvjIG864KbPBtiuO2LYWZGdpbleht1kqO0+dU2U8AxdPqddPQi8uX33yysc9ApRAoDCJaL8EE+/NCnbl/+XRZRE2MdY12G5mP9f/g//0d/9m//fu3dv33nhbnt6/uDBg+VyqYinp6eS7d69e7PZfhj7b3/7O2+/9d5kvDekXDfN0a2DejRi9v/uv//v/Rt/+S9FEUesWdUQPP4hEOWHj8yF53C+y/zrBybK3eYu44yXhnHj+PAqrrk19LdPvALzll+3YTK7N26ebnJduoub2o4Vf8MFH7KjH7QlEQBggN/5rd/+tV/7NedcVVXf//4b88dPV6sVMJliinJ8fMdX9de/+Q0Fci6MxvtqTlRVqe8ykww6/KN/+F//+b/05w3UM5fMrqo3xZP8yNq1ZtMPoE39QUh/p2bbKCfZpIEDgOd4feE6YAgvf4CtOMALrfam8+M7JvyNk0IfGC18ZZQ/IgX/JpvXOyYiAfvNf/ob8/NTZ/jmm2+//+hhyfSgCiGEuh51fWy7p5INGCfTmZl/9OTprVu3YoxnZ2cx9h97+YUH77/35PGjW7ePRQs+8KMlyA/uTfGDaevD+Bp+VATqYGMrFNLcStsf2Py4Yi3aM/xy03Y49M7jduNefxgb6Eaf7A2n8z/qs1ISRIhDeueddwK7drmKOU3Gs26xHI1GIqIKKWvbzZ1zk8kEmBbzcwOczUYAmTjP6toHzn2X+uHNN9988cUXspiIOKKPmpHhh2m7FPkcS/8mKx4ujAH4UcmnnfOUOwFSuslY+ezPldjmixNbO013f7ksYXeN9N1+ykl1s02nhmBoCtsfASs/irD781Gb3fDzURsRMfNqtepWi5xz5Xwa8tnZ2Xg89b4iclmk6zoiqqoqxsgoOfeiMVR8evYEQbyDceUQFEzeeevt8irsHF7O9vRDtivTtTtvuxO4nQQ1u/YHAK/9Kav2LMU+57nXtt21cJfwQtuJkrz5/iuCuKiYNwr0DWZ5JdPujf1cRyCXoZ5LrPRHdY77o4oeRMw5x9jvz/YOD/bmJ3Nmrp03s0ePHqWcp7NxVfucUxQmT+Nmcn6+mC+6yWx6dHDY1A5NZtNx48fFh5kAkkrgjxwi84O13aDp3e9vnoc/WC191znitkMpEcu4S5fP6eKHyAK6G+n9bD/XesO3YPwz3//B+mrhZiZqqsE7VW3bNoTAzMy8aNvYriaTkZiW0Trnyhulfgi+Pr41XbUdeiRys9E4sGOCbHZ068AB9CJJjYi8d5b/MCT4rpvjvz3N7Sz2hQVjz4ku2aSXkQ150fq0+U7S8/WVADv96DZ/wy5vfgafvzmQjLb3XnqBG0DvrZvrGazqpixkH40IlHgQOD5++eWPfeLxe/cPDyf333t7XI8IQx+7EFxM3fHRLRE5PT2rXQ2gtbeUlrem1WgURLIJkZsNJk2z/1DyKEHLfiAZM0Mn4G86CXf9OG+y12/ifHqTs/wjcsTnS6pnQycvje0aHwsAgFs7yJ+944aH7VrZtsnYflO2+quD+AOQAbs+1t0glIuHXvYf3jyJH83mVdXKkyrcu3evFBOYTqeCmLM2TYWgXSvOuVFVt4tV0RGdc8w0Go2YmYiASUTq4PKjJy/fuiMEnsjUYtLacbpxpj7sOP+lx1N+BIq83NxN7rUPjDvcXAZQkvjftFNL9q0dXRMA8AaT/wdou+N8jhcRPniRPup+UVMC1Dt37jgkzcPR4f58sVql6IxFlQFRTdEIkByBCQESu7quY4zOOUU0EO16fWfemK0ALEsA6AnyDwdp/UsnR3iO52bH0r908c57uWduXkvzLd6/fcErPuK1PbaDcW4uu9Rd6edqSAeu+32WND9qQ7sE/l+4iDZi7ophdFM/H/XpnmgYhrqq9vf3vfdD6vdne30XoYK2bVV1VDdpSG1qAWAymUjKAmoGiJSzOOcdIgNC2+4ltbbLDDJITUSec4Ibwkf/W0FwH7VdGfEHepKu2npX+MqVuC9Yp3Ta8aZsNJwto7wyadun0m5uw8vW+i5pfsh24Wa8MTTrGs5tzzlR8gOgS4SO4ODWcWia1Hdm1jRNXdd935lhVVV934tICMF7T4AgWUy3YSIE6ICmyvcObt26dYsAjKicFNeLdJXPjvN6orySNOGClfyIjOmPfA79Oo5oeOm51x6bBgB3Ja/KNgZPt0m0oXxzcc9FSkVYM0a0a8DVLcy0uQsQd2PhrnLQy4GaH+qF4brJWnvYbzrkf0Of9BGN3WiC5KLBnbv3bt+59+b5fLlcOucBtWmavu9VNcZYVZULvu3b4LyCAoCAMbNmcUSBaIr+1ssvvPiJT4gBOZdFc5LGuZyvf+7zczN9eDb6g8mla/q5Sc14lhwv/rIewK4M2+3GXSvd7BmT5MZY1y2msNPpRtADbDw0uNb5LjyZRdw/ewDth3cPrvfVh7z68l0f4XoEQ4oZ9g6Ofvbn/ug7b3xfFAwkprYZVSmlnDMQsnc5J1VV1WxKxJLNu8pyCsEfzvaOenz5Jz4fxs2w0lwRILLYc971/1+k90capl1+Lyoek+JD2XGg3Njnxk3zXHT+kkNn+9T1Z92JYL1UqvcH2rumH9ZFg/ih2PCHbJX3xZcYavril34uhNA0o5xltVp5751z5LiqKgHrU3RViJJFxADE1DnnmSej0a3Do7v7x5/66Z9cmnkgMVDC2vsc049kkP8tUUCfXdldNmnPjJPYwAGyQfkhtfJhu7hbR9NmrQ0RGIA3y8yEjvEKUeA2kzYaYfEjZrO0/QHIABlRFMU4G2fBmHBAgGdcUxkhgwKWglEbx9baz+XMSC/2EipgNowCZgRGJpJEEqIhgqoIgiAo6vbHIBkkAwHUMuayPw0BCLb/KpiYiqkhIMPQxobIgXTZPv5TP/Gxn/65swFUq+zC48UiogpZVIkpIVLX9bLsVXXIUVW7mIzCi/deuLs/mf3r/+rP/jv/JrcxVxYAIKohKPtS5RzUoJRYtfWvOeeytVR1N3LZRMuVBFDqG2HJlosg28ogpUjmpvA6MxhAlFzmSlENVbhwDVEQQzWCTBARFJJhFstZk6IKSDZVBEY0wyS5l5RAlcsTlVgNUswDe1TULvfgMIGutTjNLMmbsCpkQUNv6lRYlFRdV1S7LQ/BddSOStHHYfvvxjkKtBP7A5u6nLZJJ7xtm4Ng636u1EEjutBfN4IbACAa7GZQQ1z/uqNQXJQJQ0RWg3XRecCS+I0QgTecHNF52IHo/freiyp7UGrc4Hb8ZTZwfTKBtmFMW73HEJFGgQFign7oxm70q3/yj/+Tv/U3a1/r056ZzQxF3Cb4Q1V7vy85kuS+7fZHk1k9unV0h6rR8dG+RwuMjkBVnTNWADSH6xy5V09n4NYJh5tpRNVtHbi1dCqZcMqLKCgzIcLWoy4gM2QyyAglBQIYqAIhZjEGBKCyMc3WphmqK55Vw/VR9ywqWdBsEhwHrwAxgSZ1RM7zMKhzwQJYBm889Q0CDELqgAjEHDAwAxmgACLkHeeI+/p35pdeetPYEiKWnA27Jjm79QV0cS3is+kYN7c4wFJUa5u/pdSfInKw3uV60QloxZeGUf4KAIQ7l9nakEFEkkudl9RWRMi2XZ7ytoXC2K8NCF2XVENCMjMQWDMeBiMiQjQVVWXD7TzsSBnLYswcHCE5APvSF3/205/+9Fe//OWTDpgVEc2oYLciKWdxdWTmKtTJMPjR7f3D/dFk1S1feeUVx9iQZ0RD9A4MIBsSXBy429WFHLksGRERWFWZABGTZe88XNcMTEAJgZAE11H9YupLZkxTRmJCVRBTh0ymRERohSYVMgIiuawaAgdyOSsYmFmgMv2mWWKUbbrxlHMaNKszI3IQoxoAMw2dAEAWM8CYQQGZCVRNEoK2wiVwDwDc+TA8S5REVOgXQHboo2z6tL2m0GVZsG0a4+2/5YPHQta6kxhSbZ2ZpKBOdtE/Kptt+tx+XwAj2XwPG2oGQAEBog1N6prEiahmTZIR0TkHQCKCiMTgTLCoxIUJI24L0ZkJIQIYIxBoUZuTEiLgZktsJyqqDqSExkzLbjWd7v2P/qf/3v/mf/W/nr/75jAMQz8YKIOVlEEA0KRzyr6qjzH40WR6MK5zt9jfbw6Ob7dRckmhKJl8EBHDDevbltveNAJMQ2QXiDTG6NQFzyaaLe0yhe31zpGJ5GwApKrIVBh5C1JsLyBmBRFT1UAUTVC1VBkpPSAiSI4iPntTyDkjohGaIRF1KTIzklOwnLOIMLNn16lK7J26nDOhSym1bTudTrVXMegyKqBjQgDMymBd4Q2GZugKx7pYZoB1zUW+hHDhls64KtSqG3iFtEBI11AkbMWu4UaOGyIjYZbyIEUgKnnLQUyRwSEg7uQtKZzVBBCh7ANA3YwWRYEIiXDD7AwRiGxcU0poisxgqCKACN5vcE2l0gmW0kYIFROiRyycRQmMec0yLpjOjgFlBmgWGFRzNhqW9qmf/IXP/Mwfe+edt5aL5Wq12M6QQ6yqauF9o3o4zYez6b09mjk4Wyxf/eVfrA6OF9kUDFRJ1cByzkbIG60REZmZqLB+02xRgNFMoY/qcmygEsXCvXbR5fKrBxMxAFIzEcUM6NDMwFFWSGKIBqQgULCRvpRgXwsNxHUSMc1EUVQFAMixU7CUk2VtoxoaOXTOKXg1Z8lIMAPmrASWsxGZGQ7A3mjRJgWO2RTBOXNIqMERtDnDWgMkxzi+oLsdZumC7EqNrRxPOcOOtxAAjHBHx9yu2ZqqZLPnN/wWiQBwnccWkQDXxr4ZmgHypqqQbZ0+aGZoDsvBm63SiYqIGaho92jOShlmI1T0Bsm8mpqQmWUBRHQGIVCxlFTWtQDKOIMYIxKjKpkIADKzZ0a8NA/b3RtCsBzHrlq0q8l0/GAu77/z9GOf/8U/KaMnTx6dnp4Ow9D37fz8vG1bAO2cHpNrGrLUpcUZ1jOcHtz74q9A7VMGMQUQMjYxUVLA2rGCiggYkELRB82sAcrIYk4BB6OUzZIQIAUvoqJiW1FDCABq2cCRYwCIls0MhcS0AU8AlJMAEJEKWKlqat5Ui9wzZkJgNARru6GqmuDIAESs76Mq+ipM6mbZxr4dgDWEgOByzpYlMzA7FRgGINIQgicaWlsmAgIRM1NR6M3MjJFiFrOsCgrkgJfbhdlldaphdyXKKBHXwrg03lErd636XTF3oe0hXlhUBszbotsXgUGIqLrLjQw22V3YbW2uLcyNgOuzA8XKQQJTAjMw1HWVKwIzUTBDQ8wKlLYUhrQxBRBxyInISnimavEIGIqEjfzdFpgxM1WlGpMhJBHz8w7eeu98voBPfOEXPvH5X0wpiYiZSc5d1/V9n3MecDVp7ezx+/cffVPP3j6XeGu6t3+010WJksWUAD1QilnNgAyREAmYVDXJVjKAZxUk0ZwBlNHUkkFwuOzj1h4v+lK5nkkJnQdSgGSgCsgGiO2gyJSNs0qpuGNqWdSAzUgAwICyMaFnIKDlYL1E5xwSxZjbtiOisa8dAbnAwFms7bNqKseVFm1PpFIqd4OJCjP3fZ8peKaKBEQBLJlGhYTAPpiqCZqYQ5sgIq1tzwsR7HZcHLvfi6QL6awl+nJtY1/Q4iUgfdcRiKprfCmwBwM1vWT7w0UQTAFxEHmjbubtGIpAX2+S7AC1wJUIyFiAD5GEZoXfEpZHmIGyylb3AiRygIRECJ2ZqiK5oiabmeiab5Rn0Y72rIDLboCUAjYHt8Lb9+N3v/vWSy989nwecz5lZgQWEVALgatqYmbZHcEixNkXPvYTvyIPvtH+zt+f+DCD8zbPSvIS5uDJSc4IoIxt3znnmBkAxFRVS8imSBSDIYMV845KTk+MeXNUmqjs1JyzqjIkwCSmYjgMgwIEDEjuNA2MrGAKSshMpKBmpqYGJoCqCpoZ0Sl6RppO5su2bedV1dR1reNxUgXAYdn3wyCmIdRcBRDtUp7nhKGOMaYs5XDIKqWAOJgNw0BGDtUVL7UBKijRMEQzzGJm4EJhBWWZ6SJXThGaZkZEhUkUHuacU1WRYkETIhqAqOxS4iUijnnLYMoRAgQws5gjMxKTmQECM6pqzpmNEFHN1uyKCY0BgMyZyboT5wtxZElV7UTItEh5EDNGc44zcMyDY/CBUVEK0oEZwcA4ZTXIo8AIGZQd+gFjXQUZOm9jBkgZgl/6ZvV02LvnJ93ioc4OHp7B/ijv7fHZqbvte6pDF+HJKfze7z8YTV4copiLHirnXEqJiBQgZQPAPokaAMownDawb+MfG/3KnX788ASbKbJy6GPnECpnjfeLVetC88B1gLf6Hk1gXOfpGBA4R7fsk2dkZgO3ytlAa4eishQisHEV2m4xGo0WbVTnuqQvNHsrTk8NqPcTsf0m9piftEyI5KrlMplR44mYHPu2G9BRN6QuSTMeka+HlIJaAm27VRMaprod4mnXjZpqVvm06HPm1crMB3M1RmOA2lEAeZwgZ2MglNx4T0DLbohJjmajxWKR1EajESJmEHbGpCJOTQFA0VwxS7fWQ6G2DWkVWaY7X15gtgAXhYPMjPmSD33L/JxbQz+Fnoo0R8Rt0oHtU7ZKPSJukr0QIlopdiWZHRNxubg82nuvCoVVrJmKJFPLOTvPFTkiY8CsgtmMDBGSmq9pPHY5hTgYI9SVgYtTncYuORDnlpZxbzKejPfPz/dfqbUiuHvnDhLsGyyG5Fo5klWX49GtSR/hy1/+Xs0zUw8CKKBZctlSTESYU4I1zMQxdznPNXAWAyPAY8mzMNFHZ6dRmMzN+zQ48xW2eX7LHT+er5paqlE9LCBUo/fvn01m3siZgSNWNRQhRDJCJRdIJRti8DUCMzMxe9Wn5+9Xvj5s9rOHlmAuhBLUHNjQtbkbIjM7whwHREyiJkAcnFo/CICAijmUFLNp8GN0wFJ3uetTrhyD8+Q4QJOyDkNHAEwGiBFt0baeiR32Ma+6IasOGcRg0ecuAxODgJkOUbKKmNW+MSvfoVPVLQi3pQwiZCTnHCKKyFah3NWutkJ81+LbbbvfP6t0blW0QqCFDRfCAti683Xt3zFDtB1tsvgW0YyzxKIpF8nFzIBYWL+BECIBMhI59IyIsEyac0QCgEoNgwMBWC0fu/Ri7Xw98gj5fHX+4LRfzf2bbzz9iU9W9eGtR+88+NxLB9OjpoP67En705/ce5xAAd67f/6VL3/71Y994dvffI0g/fIvf4kRRVVEPIOKpRwLzNG1izCCprEkZ8tWCZq2g3/8j8/+3J9qmvEBZ0iD1JUXAhcgddmn+YgFMNgQD/fq4OyVV/bPF90iapI8rivHoOqUOKchDbFHn9NgOdXODylrMRmA29GdeYdhjt4PyNEh1Wyh6uda9dmAkNgbQp9UDYwdJPFVMDTJUmiDFLJiNm67pArJTJA7Ue2SDUN0NZFnzgbiHJtBl7MKZrUQHBDFNKSsAASEprCKmo0dsMnamydIaprEzEABAckREVKRe8XKLgAEacqFFreUuqWzLZHt/go3tJ00LLsWjG5ZJhGYrXFE55xKWhvXxRjBoiCYc6gqa7iR3IaFJ3ZsZqAmIqqZiDwzEWYFVAY0BREzQMiGZhI4sAtqneRVjhBtUhlMRy+m1WoYwntv923bZ+nO58uT0345lydn/vaLcv+tJ9/49qM/8kufeP+kbcJBVck/+8q3cgLkcdXcfvR4XtUT1eXjpw9fvvcCqw6SUlLJpqoF21Oz+Wl7/+G79997+Pjxajy5XTfTb7z2djevP/uFz1Sj+pWX9r/1+sPxaFTXYbY/PRjJaJ/nPbz5/fPYrc5OH37+x+/culu3y6qfL1Z9p5KiYDOaGnlFAkCNqMAUQhoSkgdkRLvr8DFqa4pBR1hpDqcDrHB+4L0YIDlDEjQlSopA3jOJaRZFx2Qkkh2yDzUYKVI/RHOOPGfTQUyNFu0wqoND88yVD4NYipCRnNOsYCZgzI6BEAxBVJCYGBCTmYgROe/YzCQm2FTAcsQX4bFEF64RAChSu2yXDRFICOEKL6RNItorbWtZ73LZLS3CGjayLd9lh+wAgXdYMhYkysyIEREVFdd9rMdZVQwAmiHnJKJmxohEnERUk5RnGTEzODAFykBAlnB/UsEYulU8eZTQxrfuVW+9dfLtrz7KiUfTOhsq1M1eOI8VnXbZwpPsn/T15z5z+Ob3u7/6N3+zgZkLdUyxT87Mbt27e376NgZiRmZOiYY4lMwrRhwlrpar+WqZc33v3qcPj6CqJ7727OlsUcfh1nz5yLnRr//Gv/iFX/zjdoZ//7/+vV/84itdql/7zpNvf+et24ezz33u3u9/q7t1Wh/fM2PszbKCAprpOhjAB3Bi5AUhAuasoDmlZKJZnXMO0NpksbdMALVbLHsBzohJY1ACdmJmgFUgM8yQSUsklApQNkuqgdkQVFUyJsmM5H3tQMRQs1gGMOqzDWLs2EBjTGbqnCMiUFBVA/BY8F7LkrMIA5PB5oTXxsjeCNOL5S8GR+3XkFBR8nBzGLkcz9vlkWuaA7nCStcMVfRZqt3olLBFR9khEZmB4QVQj2iIxggGlpIQEZMrim9xyTJzziXCYKMqoJlpzmamxOVPaABE5ByokQnEQXO06cRJTucn3be+8eDsCf7EF++89eaJIuwf74nI0LMCL5d9J/3IMgMY8be+/toXXviZ80fvzqbHGCdn89N6NLpz7+7Z2VmMA7ngfJNz9t4DkwGpqhgZcBZOiOxHTTOpwlgRfOXI46qbf+t7Lbt3X7jnF5N8596nfucr39+f3lqt/G/87hvDsP/9N85Hk/EXfu5TL700uv/O+de+uvyFMY9GNTtnLqhRnw00seSoLiUDsLRUEUspI9OQ5Kkb1QRjAIs0T71AnhHtqT1QJMfMLqeh8B0BU7FOEjOnnFUjkfPeG1A/9IJoZsMwKBJVtapaKVWLoCmbqhKlISfJYmv4AgCIGJHMIOcMAOycxAgAwKWwtpIhSEYz3CTKMjOHF+3CJcCMBiJaZCUDmKiaGTEVHe6CR65RbgshbMz2q+FSz0p/M9tyUFVFssL9Cry3sbG0eE0KIGxGJTCoRAiZSWGxMabi8AQAZiZGMlDVcRWYgRjSoL0ktaK0ZGFnYFSF0xP72lfffPKon58lMff6d05T1unMN42cz/sckw9cBdR+eXJqs/3ZuLJPvvDy228vHp2cEhylbnn3aE/Jlu35qII0ZIlKVrdD21CDTN77IQ1tl1KOfR+XnVZhVDEjYmAMlTPCvs2uYQz09HT5+hvvfuzVzz588trR4d1XP3HvzTfPztonHb7zwp2PichrX3/n4x+/92OfdyPrx6P6yaJtBY29SN6rXO35ca8GLEZ9TCGEjOqcZ8RxbqdOx861WiuNOrKksFiID2DIzKhCZUtbFmMS20IfbEhZUQEyEBI459ghAgbPiGjZwMwkqQKzJ+JsCuQYVKQjrIpNAms7mM0MzNYmqpoiAJMicam2vAZWrah2JfxgbdKamXNUVdWWpRV4rCx5CGHLAnnTdhlhoddtV7b1LmysomspddecL/y4XM+IpTMR2biw18zbe09Equq9XxvsRM6z9+vRDssu9wmjYVbMymY1ubGruiSDRAo+K96/D48f+4SNctaERweHlafl+Vx6IWDmdHCAd2/tZ3/rwSo7yovz/hvff6L1kWmYjZmhI1hOGnCQ6+DqMI6dppSSZCLiUCngctXN58vFqnPVhFzlAo8nrhmTaYTMjBP1q/Gs6vtI0Dx8tExRT88exOEJoCD4cXWbZf/xe8u7R3fi8vz9t+/PfBh7kD6nQZAcIzMR5YzAiGxA/ZCyQQIQwIyY4qhlOmE96WM+HybD6lale/thSNLHmFJZKVHNRSMPdaXgDH2oJyE0KVo/CFjouhYJmqYJjiTHoVvF1BNg5bgKzvugQOsglcoxWAl4FJGcs5k554gwpcghIDkjNiBREIUkJhsfqZmhmiuuf0Rk2lq+CAII7JjNTLIhIpNHRMmWeHgpNG/wyq/cUZyc7PfSt3vDNFWmg0mCug5JY0rDpJ6QYG8RN34XKtn6Uc2M0BMAoDIBASCsU4PUgVPOCBiqoAgpiRlQcEuEIwLMKQYShBp4yBArrqxTceQ8M+SUV4v5/mxaO1Orcm+q+Obrw3e/f/9Tn/7E/picDndv6907zTtvwXe+/g5IK9o1WDtGrruYoW0VsTpbncxmM+ecJhtEZ2GRExrs92aAkTNmW4mvEMCUVawO9WK1BMqJe7Oq7/JkzE6UkqYuc9WgDJPGMRKjBccxiyMCUoRVLeP5+SqBnrfndyeHEun0XHtV7wBkGDsmS6dnj08W+NlP35mO8Xvzxdd/g959pxtV7ec/PXz2C02G9NZ8ytwxj0/nae94supOgmdNyuJ7n9MQrDUfXJhY5UZ1cMv5cqCRI8oGjFXMEUSqEKpAqLnPnQOqQ9VHjRqdC0ZWh8O+1aZyCJqTNfVMVVKOyfumdssILXXNWOpEw6mlZqY14qJlypmRsB6iQY4jpiiZicwUDXzwZUswc0pS+BEzbxnsxVmLktlRN7GAIro1wBFRV4/f+Rv/5af/4r/2+OVPtWdzN1TBH1ocukXbVJPpxPVJ6oon0+nQRaoCJ3aOSrUiW3Np3Ch66ycqICEBAhku08BIjl1SS/2QY/Lk6lDpOLbLqOxT7fuU+9RWmDFD6nk89TGmru2bOhxODxxgu4J3Hpw/fu/RSy+8fLA39uS//nvfPDyYjipq2/D6d0+fPF4sOmL2VaU+oMQBoCn6g3Nc13VdBwBIaSgupZxjYFLLAKQqVeUR0XTtBEdwfRxyTgCgCmoZoDLCGCOAjuvKh+CIvGc0AQDPxD6IWagcGAMQEZlZ17VNxU3tZ5M6dwnRQkWVdyr6/nsni9OzoV+enh9//+3v//Kf/tQXf/rji8fdk0eOmsoTVZMhZ5yM6vZMAfeNCQnAw7G3rh8SgAO3UjhdtMveE3mHiQzJCImIfQTUpL1Eb0rsAXBIImbOOUSLw+Ccy3nwrgqVN4aoYiAhuNrr/OzsKEz2B1YIKx3yWCYzk7OYRj5Hq4yVwAfCVDOiUyEiESkeuPLiuBt8iOhKCJltEpUDrqlxK5eLOIZNSqenv/WVB9/4bhz+X/f+3L86fOIXcgW+nVs9uz2qlnNZdkMdKMYhJnW+7obeIZmCQdF816F4qkqO1xHTJoioimhgpqOqFoEco5khUqhrM1vlQZY4cZMhwXAm47EbO4dZ6gAIDAkq8oe3vAqcPNb331k8uj9fGOU2szx56YV7d24dLc4XJ09XC8/tsh3XTVXtT5kfn92PsZ1OJmha+do7x0jO0XQ6rirf971oCr5qKm+SmpE3hT4OMcamDgRYQhmq4IirqgvD0AMAAA1DSkkcBzH1wU2moyElVa2DS0klZ+ecc4hiVaDYa84ZgYhIdLh1vOc8yNAG5wlSCI13CK7KKa+Uu6Vb5U64q+rmG18/eeubbVXB0Qv98cvhlh6Px5VjsKzEDgio1iH3p2e5qhoibFd91dT7+9ViEc/OT2azmZmJoJk3ZCSXVCQZB+e9H1LUmIiouDqZuU+xJDgzy2oqCpojOjLUsZcOB25G3byVCY6GRfwv/sH4x36KPvNqXFahwwX0ROCTteDActG7FEosFGz53YWhUzRQVS2aphmZmWoW0Y0Lhjb2NxLBKz/5R+JXf+ub3/rNX/vmv/i3/t3/5cf+6C+9S6Ph8elyyePpJHDV9ivP6F2VkoZQ56Evrp+yD4gIQBGt+NANLymXqro4WVVV5UPIqKIqDtA5RD+KSxvszqj5WG2WF6BN8u5pl9tTeOutBznHW8f7fd8vz2O3otVS3z9fHM2CpHx68mAy3bt79/D8vGvb/uGq3ZvKwZ5znkZ1ldKApkhr3J4YvCNmFlXRVPZxXfu6mo0aJ4J935pZ1gxoROQdEFFxNDjnCvYUhzT0yY0DM1cVhMAisaBDRTAQARMgwMF0vFqcg0oIrqoq03RwcJRzn3IMFAK7cUVgnYoBUDWaMlXvvT+vR/s5Nm+/+RZXY2F3ds5dFD3KH/90rfr41mSvHVIytcypTzzdOxuMVNCx6LA4GSCnH3v57v1VzjkLmIgAKQA5AjQdMiS1vu+JyHuvOZpzIYQhp1BVzL6LQx8FnQd2WcRWKYR6GHSQ3ibVnrX49a+e/qO/HT3aK7eijp2y6GAOKvTAHlI0Q1UVU+ByQOzC/F1bNUWuEqMZARQfokGRp+WMyCaaQVSS6mp2OPvSz7mHr03nq7/7H/8HP/kv/ruf+At/Mdx+sU141i6ryQx9QLBRFVYpeQLjrYlTQBxEdGZmIoYlap+ZmQCRVDP4g7Er0OkgoDlkdKgENkHDUbNqoVtmjfrGW++uBn75ky//+n/zjXaVK988fbIktpTiatWtlm2GygQODo8d9u3qcfAwmzkz7Mj6YfH0pN3fP5zN6i6uum6YjWpN2RABlBmJYBgGM6vrerkY6tqNmkCaXHBM1DQNkpOcQ/Deo2oGI3bknKMNapskr49oIppmdgYZCyzi/do2C56nk70s4AMR2Lipu25gUvI8mex188wIVfDOqaAQOaQILKBV5ep22e8fTJjxyeP5+SOqw/jnf3J6cABVmMlQ5U7Z2ZC0hr15TMTgnJOkxB4Bu0EWrYk5IzDJaooZGMUBeIT5kEMIhSKD8wnUQLJEBG8qZmBKAMhUISKBDp2LFsZDOhzViwNI33zj/Hd/s/nkVERQ8zbryRbiCVUFACkZKFKJAlHb+qsLaboNTG0AVnx9Bcf2fo1HbhF1EQOBaZgufvaP/dLEf+fv/J34VN/9b/7BN77665/9V/7Nz/zyL750+9777cJcBcTz09VoNO7bgSveeH+w4Igl6Nd7p7DhlGAMapIw53NdVUwNu8PKT8hxzsP8bDU/f+P+g3dWd79/6pmNVXL00rZvv/GNXjNhBVbNz4fpdLRYnJwvzpyj2vHe3oQgzhdnKefQjCpHx3vVMkHtSfrepPNhXHmX+0gYGAFIm+A9YTYRESaPwERUV76pKaV2FGZEROxFFREdMxGkNBghInr2hA4AqqoiIgAyQhFJaWiaZgAZhoGZS8yeaQYDV7lPvXLn8cnT5bKtal8c+zH2DBUx5JxzjuNRjYG994pZLcf09PiwevDuu4732jQ8PV2MKvriz70kpu+88/SFe8fff21Qw6M7htRVNP7UoZ8v8+n8NJq5yb6A72l8EjHmvgyy+G8RgYkYMIgf1XXOUk7SFbwlpUTEaYg9GjM7I1ED08rTAmF8MuRp3bsOv/2d3/hP/5NXa5rORs3HP539uE8qmIqVnA1S7EuqQ1sfg+GtM0VVidcWsdu4ATduQ1QiYvYbyHDnTK0qAAwLnRyM3Rf+xBfufGnx23/74de/fD5f/f5f/Suv/fav/9v//v/i1uHdR8OA1UjNRAeDCOrXIcAlyA1IzVTVVZWBqhRLHACEVUjjx8ccCDB13eP7r7/+xlvf+tZb3/vu6eNHJzF94Vf/Z2782S4uUFNVVzJ0B0ej5ZPhyeN37969e3QwHY3t7HxZV1yFMUMaBX748GnbzqtRQw7ZJKDVvvaoSSQNaRJGR4f7oBhjZDdidhacmeWUiYjYDUNqmqauHWEkVAKsnB8E1HJwnojUEoEV9Kpo62YSKm8milDXdRw0p+Qmo2FtRRVgKxOamHSrPBu7JmAHBmrMpVY9ni+720f7wBpjRBiZqBGkFBHxYDp55WN7qYVHT/suLchZXdc+wO9//URx/ujk8J03htkeT2+HSdWcPorzx/MXXj6qDw5P5p0Mgw8VBl4tzqe1YyAlzIoZUIEASAC8E8mDiphh1lQAV1UFBoViIJMBqrFJToBVDbdnozfnp3cpffuv/9W77eP69isHx59Y3fmY9epy6gnJeUaHrCNXbEdUVUDY2jdFy9xGBl6A58XKWdvkzm2TyZpZgZrWFM3nbTelXuQLR/yxv9y/+a2X+5PVJ19YPLr/1/7K//HP/U/+53de+Nib7z68fbiPJIoDyBbFtBJPWXBHoy3/NMfkmQKZsdPvvPbm/fuvf+87b735vaePH7Tz06Fvc06zox+bur3gR2pdv5q7ej+zF8U7RwfvvfO9g4N7L71QLxZzgm7aHMznw0t3ZkPXd6vh4NYLQ5/6ZTqcNjqsgOohtajYVLVzLiUDVAqU0oAYgDCllLMyO3ZhuexHo4nzJClVjomgqqp+1RcpDCAga8eSZN04GoSZ+5QQcTQaxUFTSqqQh5xirkJd3tqTAzPN6emT9+pmbzKuz5ZtH4fpdDqZzPouoi9nf7nyo5QSAqPBaDz+5MeJdHW8/8KTJ+/nuKia+t6940ePHr/7MO0d8XfffjgMTXfWzh6GWTX7F//04Z1X/flqXo/p1vGkriH2i2bsmsNZ2xkgdaqrpDGBKKgAAIwY4tATcTMa5Zz7Pua1sRudByJLKWZF34zAOcvpWOTbXfdxdu/8lf9H8+T+nTt7cOs4/ZlfssPD0CcKcSUGBhJBVGu2qqoQMeesYM7x+ljBBvwuSrxLlW+GODZQxwujZuTg6fvw9P3ZqFp2sZnuu3pC1ciPJm2UISWbTL1JxS2/+c5X/uHf/f3vvLHPcjT1cMDzd77zT/7T/9Mv/Rv/1osvf+xRfzad7BF4RZ9zZgLPCCasVjsCxr0GQPM0OM5x/vj+0/fefv3733v9O9969/uPYuxj1+cUwYRMK+SK0LXLYZT365MW/NyamrrR+PC8e3q4x/t7k3Yxn8/rFG082p8v+vGkmY4txzgek6bzOjCjy5bcaMyrBTnjqur7VtL58f6tmmaPHj5BCw5dH1PstQq1AXWLVSAL+URWjhkV8tDPEWkUICUej1QVc2L2jBgJh3HN4ypEW5kJow3dYjwea3QPHp54OkBnk2njCAwEULJRCIEsEATv6jrAwRTnc2nYpTxo7iROXrz70ltvvM4vvxhjx1yFCgnzHlNSSng6mkq92OfkTx6+HydyOK0ZD9uBzOaTpoI8+fZbD3sXR9X4rTcfzYdV5fedNR//JP7YTx//9u88vv+OWnyS+/uxffxTX/zJT3zhJ959ekbjUTaHwQH7LlsWYQcOe0IFqTuAaKxmAZD72OXeKvfQ9l7MD77z//yPu+9/1b8cRvX+S69+6c39n/Ln57PZJGaK3cKhM/RmZNTkbslVMEeAmkE0DRoHNIDMYqpMRM5pytGk7ZeDCTr0i/69f/B33/iHf39+8vTw1rE4qvf2eDoZHe2/8Oor0QQOPjEK/muvfePbv/s73enj4+lkUvGDRw9DE6bj+vTRO29/4ys/8cIhh5BWT0ZcH4zUsrAjj5DjIDlCkpzz6r3lW2+98eTBg/nJ0/feefPsySMZ+pwGpKCqptmBEJknx+SJKMdunObC94Rsv/Ij79nlvs0AMKrqvu8tQ9cNTdOcni1v799GNnPiMDSjGg36vk8iAWA0CiGEKDnnrAKg1jSVgdS1CxUBcozdEJdEFIJ572ezRkREBBARCJkJwQfQXNg9Be+dB+8oRUPIpiBqIFDO6/sqjJqGAJs6FHWemRk8EaUcl10XyAAgpTXYgYhMyK5Y/XWM/XK5HDXVNvDAMaQkxLq3P3r0aJ5zbpppkhUOHemiag6nsz2N52+99XrsclNPhn6lJgjatu2w6vdv7f2jX/vW2VN+7Su/+ev/8L/8c7/6pf/Bv/0Xp3uToMuXjsKTxfmQFIgpNOgrQFJQoxo9Dm20kprBsxkroAsj8OgNzt546/zJg8PZ1Nf1qo2Pn7z/iak7OxM7P+fg9saTDDakmFVW2k204YxQjg0RaN2IBwAY2nNyThkdOjd0Z1VVeV+lZI7ruqbDV3/cvti+9/T12juV9OTBg8V7r3uE134j5ZyXLXnv1XI9Gr1y99h738d+enjUt/OcB8K8eOe1d74cqqOjqpn22b727mt9u4p9v1otzk5O2+Ui9kNKqT3vz87OELHkayy5oOq67tsVM3hiJEJTR+A9OeLz9qyZvz/9/B978Ois6nM39HvTMG32HfvpZLaYn/d93/f9wf7hZFzdub1/9uQBOwp1KHHgiOi9G9W1d5mIAFyKRqRELENLmOvGO0fEDFipqvdcV54ZwUp6FkNgYgZEduoQc2KRTITesw/oHHmvcdA8aM5KBpmsbfumaUajEaBWDochSxaNKkTOkamCigIUhaGASqpZVQgMVMbjMREtl8vDg72u6wiRqKQ41BxX49Fs/7B68nhpCCFMHCyr2rOzdnnat6eebX/vICVYLpfe8V41efSobcaHpyd52caAR/ns21N+cly3d2d2eODDjMVVE+y67NqYurxKGoGcAVk5mUsYmLIpMJtRygaquR32G98+er/GAbzrzqVdxeU7r7/87pv18Uvn8yVSqKoaRMeuJk3dYjEcAlpmVVAkcSomglm1cs6YzHSQwY3FfNSUDQQjSA82Pj68+0s///n6S7nvKOez99+L53Of8uP778W2y+38fDFf9K2SWrvokJZ954Lv+tyen1VM/Vfn//yf/hqOxvsHt06fng15yDmDGZrmnMnAOUeIIhkRQ10TC1fQVIEIo3aTitmhQ0I0UyQzRmOyUWPnb3yt+bl/XdnGLgw5M7TI+2Da1FXXOhELzje1f+mF41HNc0xNNfIEcVihwf60qusaEVVS13ZqLg9pPNsLzj9ZrUajmplVMxFOxyN2WAePBMPQLZd9jEmNPXkiEhBAI1ZSNpOcLSYTAyJQxRijRDU1Ye5ikmUbfOW9M1NC9Q4RQFKKfVLnQghNxcOQhmEwQ2YOzgVH4KjymATY4d7e3jAMxadsZipJCT3xamgdDce39lbLYT5fHh8fTxtMKl07Z6JbB4cptp64S23K/WQ6m69adjY9qJfL5ag+yF2av/+tj99qvvu13/4P/4NvfPrTn/3Epz//wquvfOpzn8dRnaFeJVn10uXc5ZxiiYgIINoOfUYHfsxIY8+GlM7eH97+rqTlw2XsVxZB2/NF+M//3x/7H/6PR+PxYG6xSqpQIXo1hyHOOwYM7Dw7MAPymTAqOGJBSMlyzm4CMwO1xg7HQVK7+u7X3vhbf235zd9lf7B3sJ9RqHbZ42Ca0d4/e/S55mB6uL/vbs1Xy9XQN7Uj8Ofn5516ciGnvp3PPYgs0ny1kqyDoZnVPnhfmzOC9YEH54mIVEXS4E2apqkrr6reABEdElLJoaNmRgCumvRP381n94/37tnTXI+btjsZHxxrtwrBOUchBDNpKn88nbXt8tZew0yahRDqUZiNxwDadZ0RG8JysfR1dXR0JKZmNplMAEhFCVEJSDFnTWlou1USJwrMxbeBINkI2CFTVY6lIoJZRnRIgGTlND6SjzGeLZb7+zMmYrSmCUSF9LXve9N1vAIi55xF1oH3ZkZsTCRgeYhHR0cnJyfz+XwyGTku9iIhuiqMJUsdwtHh7MH7J+dn8wa8axpSkywUQsVjERu6bjQaBe+X5/P927eNVs3IcUqPHn2TczdqgCUtnp7+3tlXfuuf/c7R8fFP/exPH9y9d+/ei4e3btfjyd6ocbUvjo/zPs3qSkf1SnkB7mS+XLz/kLozBHv8/W9n6Y39ZNR0Ftt+8fZX/nn94suf+cmfuX38YudGbjpaxaEf2oPD2X5rqtkzGtmQY6KMnlDNVsLOByYy784ciA7SRR9dDTAd3737qZ9ecI2jwROmvjt59Pjs/pMaq1Fobi/0YVqKyHQ2Hk+n5jn2Q8X+cG9P2+xGdRoYcgzex5S6GJvKN6Bm5j0ym6kCgPeECKaEhozsxpPg2DEUQoTgzAytHCC0EodmZkYNYqYHXz2+ffSwgkmoz07k8Jj9XlM3vlstHMFy6JA0eGx1mDRIREzVGmQFUVUOPg1KrurT/NbR7cls/Pjx47oZERECeUcqkJPknHow1azqEJxzwOwKiIiIBMxGREhNpQoAmZiZOUVlyGBdCBW5Kknu+z5ndRUx0xB7Iiq4tPMsyVLSvu9DNSqRVeuAFVBGNJDATiTNZrPlctn23XjceB88oyTNkkfjcR+HlIc7t6ak+uTp/PEjOX4h1KPR/Hx5dracNiE4RrQM2Hbd0cGtelQPFg0xd8vlyTcPxoFQkTA437UpLpcn8vC3f/2fzPv29u3bBwcH0+n0YH+fCJbLZez6vbuv3D2YjZtqbtUiTO8/ePz2N75Ki6evvnznvbe+u3c4hmoSnDdIt+pxur/853/9//q7f2vyK7/657/ws3/04fncEKZ1eP2tN+PjsxR7BwI5yRBHzeTW4fGsah7/zC/xaAS+IiTXu1QZVVBDpD6SO/zUwR+/d/Ary/b//r8/X5zduXN0cNQ8xQn5MMQc9o4Qhr7vV13rmaqqQiYzG3q5vTce8gDNLOcch6Fxrho1MSeXk5k5h8xohM65ug7M7Gm0Bke8D8EVyiMiCgQbZLQkDwFRMwuuSZBX3/ivTprp6NM/HwQqN2oXJy+9eGu1sqNb+ynqeDz2TKZpVFPtvHOOfYPIQ8wxRWAgZumGGLu9/f3p3qQbOlFFrtTQMTgXUspmBsSqaoA+UEq2Oe6WAYEYwTAnMxuIXAHLArEqDEMa+qQq3jMH56LbVGAAIuCqLsbKOhbGu9Jp23UpSTkiV/nQNHWoSDUvlxkRybtmMjbJKaWmdkTOnDpkUPWOCSFUEO5N68rOnnTvPXjv+N69u/duLU8XmlPX9eCsHVpNerh3V9VCwJzAUpw/en1qw95s2g/d0Hee/fHBHpqcPXnoq2r56OH5++8x82Q8ijGdnp6mnK1ujoIPnls/3vvMTylX73z/O/tp9e7JO4q5Bw6Cytm5XNfj4WgEGbuu/0d/4//zj/+Lv96EipkRMiPZuES3OMk5roa9er89fnFcT/ELP8OBiZ0ButkKDJJvnI05Uk4uEqoHN3r17tvfPnn7zW/v7U3Ol0/Pzs6m0z0VeGkyne3NTk1L7phVN/hmVE/3m7hSsaEojkR1U4tlGdSzZ8Z61DRNVdzopepMlo6ZzVAMXKiASIrgTrkcKS+RRIU6yaCyQLNaHr17/s63P/nzf6J7+Pho/xa41A/Lvh+Oj48ePXx69+6LVYUM2TXV3mymAv0g3ZCRXT2qouS275B5sWw/+cmPG8Ljx4993XStEHtidR5USb15Xw05pV6yAQITIZFSYY/IOZmIsjNmLmeriTxhgdzAICEB0UVOEQBAWCfgUwBNeRiGNWIMVtc1swAUbssFFU6xS9mYnIhWVZUjdF0XPKKFyTSAufl8GYJrRm4YllVoXv3Y8ckEvv36azF1IjnGfn9vBsrnqyf13q2xw9VieXB8EDmPp3tPHz06e/TgwGsTuKpGOp6kPg9dGwLxrBkEHKMiAVLq42K1VMODg+M295L7IUpscDqduvHee0zaRWiH5ODkwZPDKfCYc3fmelHYq2XCWO3PkBwx42RvFJqwWM0PbebG9fSF2zCbzgVotLd/eI99baNRaGoNVRZwK0xIaOC684WZZRJNORLJv/aXX/6Z84/nXMXz/o2v9WkOsz09VV7ePz85xWZUEbkQRqNRRgPEITYEGDDPDpqm8c4pQiLwqR2p5sqz9w4AjBCJFCxrZBcAAXJ2YqNqhIjDkELl0hCrqnLOZZVsAOgKL3WTo9XBj+0fvDpensNk//7Z+6PxTC0fHd8CgKO7Uw65mlQcajOfqqCqWrG1uW9zbLNENB0Jru689EISHZIKzfoh1zWM61SFIGsrk7MCGVSOVbKgEjG7dQIlM6AShEbY9y2RKwBTFRx7v2xPqZp4FzRmUGua8ePzxe1b00nwGqHkAyrIjopJtpxNQEWFyCrnQ8VIYirOwWhUI7JkyIMOORFRm3AwMetG4/rwaJJzRLCmGqUk1ve3DxuHLzx8dG5dN5tOiCgpIoRp8B5zmOamysNp5snq1c/c7vm40lNTzH5EDhz2oRovlhHGt0d5qZIUjSyb2SygeQ+5G0+akbENgxtXTx7fv1PXOXZgab4fcBkPvOO+XUCYHL4Ipiqru80kT5FrTu2iNpQEj7L+4n/vv59ufTLOZm0zacZ7Lzu2wSJAh9Dls7txJI8HHDdONDlyfV+SutgwDJ5YRNwTR0cvzUMOw7h+7Rv01qNXvnhMn5i89tV3GYARGDE4NkJLMUluJstm6p3bG82OZnvHo/GMKIhIJ11OEQAYLasiIjmvCBr2yooWL1aKQkSHIfSWc84lkj4A+FBzVTkXhuPboRrNuNHszY19m1+aNNMmxHHVNI0hhIGNzHlGBgACVkB1ADRxoXJDr91iGIb21mhUeUxD7LvWJ9qbjCcNOYy9AiMBkqjGlHPOaApAJSsvscFO9Uoz07z2eSGWXGFmZiX0AXZOxkHJ1CVq5YwB2iZ8EM2MmXMyBPK0PnHmPBM4pGrsvRmlaClJ18ZsGgeEQa2XPmLTqPNceWRmTyXYfrh1PAYWQHGBFZMtB6aIRMyha5cuVL4RAXR182f/wl969Pf+z7cPJiktcuyrZpQGPTwI3XCeQ6PqCNRMRCQN62j/WoFjBnKnvbzywivi6xde+viDb/3e3RWNmn0z5ZHvNMb4ZBbC7WmzyKdZVTrTIT5Z9u+994T27hy55t69WfL+bFgNJ2dp0cbzZe3DUTM639vTru/2p3Pq1+7EYRi85/LB1U2JR4hDWsa+qSu5fefRO99797d/9+T+g70GQZQAyTmVRN6NHIN3zeQzYbrvju7y7Rf83Y/h4a3Oh2WUmVeLUVUNkcyQidkTgBkUgaUAiFghq2oUoX6oy/FtAADwVU0upKw5c7RcOa+SYkp+gtN65oA6W2VkIASvgBC1t5JgshxmMiCmyvt65KczJzJySb0jy+waZ8Ah1Jhi7FaOQhITERHFdTIP7xkBlLicA4ZNuP76ZJEZSi7EWEJClZm9Z1XF4hYsr0AXUYNbE9vW6ZMIkwaHocKqZh8Q0UBBBZWGUo296O4kRuRUNeYoLQxJghfniHhwjp2n2uHB/uSW51XXMuFqNaDBqB6HELznxWIxiKL3YtqJ/tSXfuFrT998963fe2k2G1e1auDAYKt6ZNGmVs5GmaWUYj/EmFQ1Z5zeOj6dn7/6+S/cevHO1954+8XPvlzx8uz11+q9sUesaxfEJOUqkyYh6V0yHWBoW2P38idefTrv/rP/5D+6VY+aZuwcVTXFtDqfPwWB4KqXP/NFz3vVn/3T8vEXXXm2maiigarqMHRmZhNpn/SjepKtks//5MErL+OT0+OTVXLYhMp7b2bZFAgpePbu6eG+VWPzjXCV0JlAnOc8xFRZThkRS64VzAxMphrMEE01Fk+89xWaWRZDQgLNwkRqFmOPlPuUZoGHPAiokCI5V4+z+W5IJpYhGjB6JMSsBgDknGYpRnfKaZAOEZ1zHLxWOGg2p67xgGQqmoxcVSWHMYtEJmDHTB6YkEBT3sZEAxCAIUHJaInAapqzlIRQORsiOs9gCuvMCEgE3nsiyKaG6nCTjcg055xSchR8oLqhuiJ2ImKiqoLBo4J6R3Xjs0rMamZZVbMTVUlq6DNYoDAaTes6NN6FEFw1GU8Ss3/84KkDlejZlJUZXbfsXF2xc3GIOBp99k/8+fO/tUjDo7HPvYkxoowmfpxTKiE8hgBKecQx5hwTORZJ9X5DI/8bv/3P50pnTfVHfuVP/fr97z7t5y/O9sfkieqz2Ec3WSJWAyLirf0J3nZL6yb741fZt+er+7Iyi7VRXTf1bC96SgvFgdv+6RRserKKd9ABQIwxOBYRAyWivu+dc2HRudpRU3URZQh19YK+fFc+6yBhTzSUJAUlDyChmU0GMwPNJhJFVmrJsU32Ag8e2DF79s507XcXsBiyiCCjc65PaT6snHOT2SRlE5UYoycu0aBVaNBj27VV5bOJpAgmw0LBAipLRSKiKRERkxeRbMoZXAnmRk8kCiqacx4gD6CRyXsOwGYIZEyIzMExkicOnLNmUbFsZmJG5EqUgFk59UfbRHDEUDLPaTkNLYqIgYkAiJhZvfclyIAILBsoCptHKmhlyeg+alyosK7ZeS3JDQlYGcSIiBy7sQdXmYgoQs5pcZ5EULIxs6mZsne1Y181HCUbSdU4Zpjs1d7L2dmJZTKz2ajJEj16Hzygt6x7+/Uf/2N/8tv/6L/KclJP7TwuHFbLTisaxNaZ74iIPQZEJuLUJ+K6rif1zOe8X+8Nfer65k/9wp/66ld+Z0h20i8ODvb8mJKPqxh531Oi7LGqnLTy9de+5o1fPLh7a6qTZrZ/cPvOpz5TvfTiuYV5R0NPe4c+jQ5aOqjPnSOCsptjGsDQOdJEiEhpMj6ciuCYHYYqDyv1cH9xdld9OSlhZiUxwLrSILCpITgjzAoSgQmceTWnhqosQms0BBEQSQOTISIoOEBkJoI85CBgRpyw5qCqMVrtKGVtbRpCI7EHn3xwOZcQZY9atocgAjEgOhQjpBxTSUPsXKnu5UWSaB4Zj0dTJt+mIabskEgwt9b55DnUdRCRYUhDyqJCCMweEXYTFAKAgRpkZkJHiE6Rcs5mQuicJwL0xENMwfM67RGQKpQROueco6YK0tSq4AOWo8BmyYwA0DkGoDiIKRCbY27YIzpEy4aHeweSbcjmXYgxIsFsr1LLfpSJQSED9kPSakb7x2OuDuYnKwcuhEkXB8FokoKr0WzR6/FLn/3kv+ICzC0shCT2OCysrlXBRCHpOoEUmphoMti/ddzm1Iz2n1bf/PJv/earL7+Iw+OvfOeh7L3w8s//xJP33zw7e+y67jjwS03dDb0SVuRy341AXrl7NwnPO8lPzmKjq0V79uSJZ2qXvUYE8fu/+u+c/cqrq+yOHnQOEcuR7S1+UVWVqmZXoYLN533WriYyPTD3sWYWW2dABqSmGnNWdc557zNFYGZ2SI64BhZQ7cW4XikYsSmLiKAJEBGYrHxVVVBywxGN6rFabts21nXlgziOnnPO0QwcdTFVhtL2fb8ixwaUVRRhmZcjXecVl6wmJZ0LGDliE7GcJedM5USXZhF54c6R41FMOvSxl1h5DDgidv0wT5iYiIgcEvigXJbnUgLfbaSfK8ncFYpALzgrMxOBK0fwEb33fd9KihYCIJtaTpIpM3vnyJfzyhYRi3rKIoJASgCgzlflvHHOoiqERkQqhE4I0aPWAYNndjqeWduuYtLaV12/AoC+75mZA0+PKmDwEEydU1oNKQTGrEPbv/+kPR2nV77wY+w0pWFvNh2GlLKCCbHPaDFJSglAAzEjnCmexC40VdL4+b079dGetE+poerHfubjn//M5770M08fvDe8/4BOH+eTx3F+tkduNfRN7Z+899bp/fsB+filV5qPH1IHUNen3fL09Ek+exykv3Pn+PB4H09OJosWJsz7Af9vv/12VVWxHzYF07T2oR/aGvic0zRUOUscT6qM6dGZ3xuhw5IUlJldMUdKikDMsC7fZERUOQ9gkmOlewrm/Pp0X86RUQ0EvSvHAgyknBNwjpg59jKuq75vYRPHOZnutW1LTYfGEs3zCM2ZQF3XKaVEqQTbguTNMTdAIBEpBFZSLYok1QxotUMEj1SJA2MDZeoq6J1pykOUHCumpmm8d9k0pdSnBAAqsLG1ucSDshMwKr5aARn6HAcF85N9V/ng0J2et+ervm2XL9w+3J/WvXBKg+ToGZwDx+icc8SAiSggkAiaIiIaqoFYeQU0LinFnfO+IoOoHRjGnEajBimFEewfVGfnj+vRHefc07Pz8WRCDF3XDUPviH3gCpvlYnDBZegPDvYXJ6uT986hxaNXZ9Vtd3q+wNxI9sqp13mVzNcN+hAlx5wYaVyF2rvVw6f14dFJ1wI6SurJgCRaDOahHi8Ehl6n9Sg4mndnFhCTEOaQzk6/+mX4zrdOX3stDsPxSx87/NU/O3vl47h/1EfoHp0MJ/MwGrvZJDdNXY1XbUyQ8a/8s++UTCzl6FrJsVZVFSMVjLegM4WVmpmkYZvdb/svMxd9zntfTHhc5+nTEGrVDABIpqpFGaqqRrOUrFpmVi4oA0gpOeeKpbl5qIhI0zSIKCIx5s2WCESEllSLF9o2Vm3JH+RxXa+gnP8gVc1ZSkK5wA4ciGWL6nJVQf3obB5C0Cyr1UJVx+NxXddm1oBPaYgxZomGCMTJQBQYhqRqyjlZ16Y+JkKu63p/NIl5HsZ+iHr/nVMCvnN3fzSSPlGMWbI5YkQWSZ65qryWsg2UkYwBTVky5QStwKhyqV8hpKYO43HjqzCfz0MIgOjrxhOa5mbkeESD9uxDGnokC54kDk3TNNXo0aNHXE9SjA7Be68IgCxE/TAQoqqO66rve2Y/JNH10S3x3otIWYghp8lkMgyDmpX5BwBynPOaTlaLVkTqunbODTGW0LyUkjiXsqLhhKFeni6++y9Ov/Xl9OQ+rtJs0rz46U/mFz/dv/KT8uJnzoaEKtXQl8MOROSaqs45E1IVKgDIMSGAZ9ev2rqqyvhyzmGH2kor92+J0rEv+qVt0g9tVc+1V6bEvjOUd/OectZtmCBuDvJs2464JDNbLpfbhBylf1NLKY1qp6pg64QcsE1/DQFKGu+1dVV2XaHSNQ821G3tPe9qSdkM6noyDMNi0Q29jsfjDlokDCMfwPfd0A1RFDhUqeecLZua4rqkDSM7UBNDQETvXFVVOUrO2ZTKtICZKaqKGcasSXrnCdHYETMpgIoBGIdQSz49eXx0sDcZT4kgS1ycnNw6Pu671fqUkyEAiCkqrCEUhJyzCIhozF0SCqPJ05OzvdlkNp6o6tli3g/JnDMgRhJNDinG6JyqAbEncqvVUOyz0WhkZui4EICoMTMAqoIlAyBCkmxN0xQKTin5EJi9mYUQcjz3HAbjlaHsHY5++pdGn/q8tovhm797/sa33vz6N/A7bxz8xPLAyE32U+C8SUFQeJNbszrmnPM2SUtd12vHbghrAGiTf6PcUu4vpLCxdTbpVjZEuXX1AiqiI6J1DWyTcmgIS4zgTpq1GHuzdSWEjZqLiDYajTaMmbZnO8yoGLFg6wehriugMqMZqNo27wLR+pCUlgxgKEC4yd5pwfkuZTNyzplzfTtfDYOKc1XnnKucZyT2LhjEIeeuE6kkGxggE7KyIjrjwKap1PEm8k0dlqlPSYwqz2aESWVISdVwk8jOQIqmEaqmWOWqAtA5tluHs6r2dR1ijKtl56uQs5bU7gCQTdmwVHYyQLVMBCICzFU9jjHOVz2hq0dVPWqAKcdYIkIEHRCaaDnPVXhE2dZb7lAiUFNK5NdpdR25EobsuAA1hfUw2FBCF1S1GCfDkJ1zY1f3ZqRmLiTnB/K6Pw63mF/+mcmT+02amwlMj0+mt07bjB00HAubg5J1raoq731x49Z1HUJIKVV1vVqtdJMutXwIISBZEfewOYS2NkhLjTUAAOBNmS5EtJIQw8BEt2nviahfLcthIFAoJTXLr+X0e4GZ1/4SwLJ7VDXnLBI3ROZK8NuWp675q5YcWHkNLZb9h4hogKCGRIiAxoBMJOXtwDMkz3FISYC9n8z22uVqPp9TxVVlg8uEUDmuQkM0tG1WE2KFkjKf1i/FzGYZDEQMAbx3iJZSMiXUbJsdcqH8KGSLSAExSCbJZqZKAqCjio8O94Y+rVartu8MYTQaxdh7R+bYEEARkIszCYibYM65wEyOidhEE6iKOs8xDt1qlbN47wP7QRTW5xghBI9oOWdTyZpFrcQxEVEpilMOajrnwLDve/aVr9iiaBYmZsdDr8wcgiuVeERk7eHHKZrWrI4dgLV9n1LCEMJ4ppO9RHuZvFWVMzygYUb62C7cYK5ynpkdO1QzdoFdYGdZhmEYjUZFP1gjlyGICJjQukSi0SYzEBroJg/qVqwXBmBrkNxEUjEUSvg27rRymK1wx5IJCXF7pGiddrXrujJZhW1vNNH1WbjCm2GT/1JVS7omIig55rZlxwCQGIhQS3oaK7UMwTsIGSKKiDJzM/KAleiw7F3OODAQac9aBQkOm6ZZDb2JqYqJmmYA8OQ9eUMhdADEgHVwPpCI9F0OTlOSlEq1hMIjFRGRXRUaQj8MKefsHDSND8GNAyyXS2J/vlia2cHBnkhqRpWkhOhE0cTAMSIaApGNAodQWQ0pyXzZmureZAzIj8+eqCoThRCcc0PMOSt7VxJ1FCmnmh05E3DOmRIAjMfjlFJx629QsMwOkLIKqCZmdA4Bsve+JHhHtHKGuKoqM+tTHjU1W0790hnseVJ2ImnOZ+aGSrkCzSlFS5m63mFlh2WFRMR553LO2YyJgveS86BKREykIoXTMBGYqYiprkuObJhiIYIid9Ynmg0KsLeVmyWIQTXbJucGM3NVaEuIuJjha0gPrXhE4CKVjIKZX4fRcGHPZUcSQpczA/OlZNXFApNSEqvQoq4LDQo5j7aOjlMzWmcNJnbGDplZTZMmyeIcHRzO7BSXy+UqDyEE72CxysFhUwd0oGBZVPNa+lc+OMYYbZ3OwaH3XNeh72Pb9ePjadJeh1ROqSKDd84HBnM5STssRaSu/GTc1I0jNjPNYv1qKVmLGeEdqESgklQWCshgBKW8okgeYgaAnEvsMDKTqtSjMag5hMqXbLcZcF11Si2npIVTkg+ISOiyrVPjFk+bbur3OAfjcQNAbduq5HrUAGrXDiFURevz3nsE7ypm7roOeCnWi6qgKjlkFHPgQ1iGSscVCqXU5qhA1eiF0XjcLU9wc6ZxbeRubF4qvq8QQl3Xq9Uq51xVVVVVRbjD5UzSuHHmFo5I68RFsOVba4vEykmD7XFeVs2mWWVL2RshXzJgrX0nFxRGjMFXZaiFC5YHXWgRsI4gBgAyMBGjkuHu4tw6rivBbjZVcfkAFXXZCzM67zFDykkFJDjyzh0cGCGeLzTnmIQk21IFzvOoQQDAkuPKh1HtPJvGPqmAlCiNAYmais18TJLVyLGvnUQlIh+YGZGgG3jVtxKHybje26/r4Eyy5BQVCP2yHeq6Ho1GBFhXfD4/D9UBogfQbQayIovaiEQaYyai0Exzjou2NVAfxinGLGI2mJmBMqNociXHpAkAigg6k2xMWhaxL9IWkZhKLKJDJnKleJn3FRilqGYgkpnXp6hDCACWUlJVhypDVEPva/aVKJiBC762JCA9CHg09BwFcrt80oPXdeacEqZaTOyCsxT6K/JlXVSiuGid2wBGeWvfbAkUEVFLlLiBGZfiNASeXUqpJDlFxKJriqjkjGTE6NhvAKa1HB9ii0AX5XNKQR2CdRHfDUCNm2TsdV2vtQXIa9sIAAAcbhO6QmHVRIDEUQ3MqIADjilzBkspeUfM3jvuoikkR2hmfd/XjR3fGdUT//jpar7Ips4yxZhWy8TMwXEduK7KSfkUh5VQLVHMLBP6QC74gJglnZ6e1nVdVRXX5Jwjgth3q+Vi3lZqMpuOj2/Nmsp17TINPREh1o+enhA6Ju/rpq6gbRfjukrrQkyoqgLoTM0yAUbgOtQ59QjoXOi6NuVhMhmlJADgvUfQAp6E4LIKaJH8xQtKG7UHvOcCzRSrJTT1YrFAxJR0GLok4r0PoS6H3ep6JBKbpokxxRjZXLHTqqqyHLyrYpZu1XnOVc1OY+oWwwjEwjAQKhEiaQ4uAonSdCsG8W+9tihjwp0EawAgmrbVIbYoT5GbW7lcvim/brnprtHNzKVCz86evkCUtnxuq4kyc9kbhREWpDPGWEa4++i1n3Njh211ie0uIu9om8sdLq5BhhgzOl9iiDxVw8L6eT6aUQaMGbuk3ZCzGgESEQh4puDNLMVhWK6G5SrFpPNV3fe9iISRrypGyoCZHaSEiAxAJqalhDgyIrnYHt4aH9xufNBhGBaL1K0sDmS4fPHFo+k4pEFizzkrcPSNvv8+erbxmCcjbmpfVZUZdN0AwRn6FBUEGk/1CKnOGGy+XIUQSpaVjc6tZuYJiTmlNKSIiOh8UbBoM+15gw5aibDZZMTdugnAkIhEcykV6r0HwyGtI2k22crBOb9arUIIzJ7W3Ee20nU7JEQrbCirmK6BRVcFTRdyuMA0FxKZNvHSmvIO8mJbxKew1S0MVIjSSsH3Up9+DV8DlOrt21ysG5tmC0Ns6RLWedkQDXbhpLWw53Vs7Fan3CXEbR2gjSq5Lsbj2V18s9UNAMAuaSAikpLkLBkqRHZsTtER5GyytucUNIOYI/WV23NuPIYkeiDQrvB83q5W7fJMAYjYM3PR1giFSF2wUJMPzjm6c+uwmGjLeZzPuzgYYajr8MJLL6YksaecZIjLkkj34funWYJ3VFX1bDZhshhjjClJLtqeqoJCARXKi0wmozKRpRoBbpIgI4cyk0U906J8I9IGCd91jlREXdfZOrhEscSbECKCAJTxb8l0M/mwwY+5FGkotLjFsLerXyAUAC0LqmAGa8LVlLdCDhHduuYhlOxqa3pChG0Ntivtiuze/XVja++wpQ1JXWGKqro1orfflB6S5GK28yandWGcG7fh1RJSmyIma/t9d19tCVHBtiA5bEIrEI2Q2ahUEs+GTMhMlaoQZIIhmyjCJkdy8Fh5CpWragTADN3x0Vhk3Hfa96qCZmyKVUkxz8pOnUfnAJwRQYwxJV0t9Ox01fepqnn/qNqfjZ1XGXC+GNSGusEM/WJufReaMYxHYTKqiEEkZYkKtiYsLXq32UWhTAjeF8gMdzKCi0hOGUqUKJiZlUq/zrlqNIoxllkV1ZSSrc9L1VuqQsRNym8jA++cgMUYTc17r1xqNpSyghhjKmtdYiFWq9V2CczWThBEKhawqpqowZqyAcC5deZyVXUlvfmWOLbr7Wh9hVopt1n6BTRF03JCFNfFFxRUVC92xm4/WzmyJaOtvbJLXoWatRgmoohUojuLyiNquA79vlyH+rr+15x+p39EBIR11XkqJg5mI0eEQojgPEfFYEZsgUi9k5yj2SDqkbVUvFUVseCEmQiNCJ2z4Klim40BWEuVvlL0Vg0BXBaLSYZFiqJ9T+2q69sUQrhzvL9/2Pgqmp49faRmlMW8R0V3fr5YLXJVH45Haf9gWtc+DX1RpdiRqhE6ADEzATTDbIqmZAY7srIQ5XqWnFNVBeMyD2KCwMyr1WpjpK/NC1gnmgLEEgladKHCEKRIc9xhe2jmiF1Yq1IpS3A+loqnJSZ0R4IBoKqJ5G0+qbVOuMlXn1LaUoLzpToibIl6k2kNLnw+V4hsK9Z3V31LGbpTGw/WpX1tHQ3OJXyrCP1t0ScwM1wLImMmW5OOiiY1RMWUk/feTGVDaripaU+4zo290Q1gnbcYzcC0FBrfVKIAAMJS3x4or88WigiiE7NkigAeqfKcjVpJmJNiAPVmlDSraE7qKCOag2CQiCBUzB4taZaoKiooBjlBin3MGAcdopR0Tt6549vj6ayajCqD1C6GruvS0BgMk1lt5B89mrerPB43vsrjJtSeCK2oTAaUU05ilbN1MqoNx6Htft5ob4XVrSUSO8P1udA1fgfgnEv94JlhazgTFaA4xoSb+jVlcjYa54alIdlGPBZFv3zw3td1DQAppRgj8YVqQZt0aiJS+QoAdJ2slMs6IpZ6cBvxHYdhl83YTivLXJx65VVtJ/l5UVwLUy4LbWscZ61QFjp3fOH+2d6ISAVH2FLzLh1vgKSLL4vgfpYd7nLKXbUBNqpCwZZ2qV9UEEmLig2omyIEWoLb1NABk/MeGp9MtBsSQCkRzgLIAELmSNt2EElA6L13LuRsMaEIG3IuTdfoGHOoaxqNYDLyo3Egtr5rl/M09Gi6x5Srpkmaz8+Wy0X2rqnrMJrCdFKD5TiUGXbdMHRD8r5SLAHw601IVMRlyY98wYQQgZlKPY3tym7pgwFHo1HRJgswaWaloltTVdvZExEmKvmlZZNyl4gQKauq6pZhFbYHxTsYnIio2O5DC/mirXU8AhS74GIFi9w+14FkuFaYOr/li89S6vb9t6Sw4VyXiG871t2et3O0S0Pbd0O4sGy2emcJPoJN8cZdKt8yZtrZvusp2D5lt6JKVuKSqUm996rGgOwcUBJFNciKQEgsTQ0OUUxTFkmgSgCowCIxI0z3xjnnYRjabkjagTnCAIBZpRg9lSfvKAQOlfOeZ2Pu47BcnUs2U6fKYKQKoRYB9/Rxt5i3o9FkPHZNgwf7Y09sZkPOiGiAccg5a1V7BEYUICJD26R4LEmIdudza7+WsjRFLyciRN6SQkqJmQnRNjBzCcVYz5VizpmECktbp9DdYhjMxVBtmnFJ7grlgJffYI3sdxESImI2IrctsEm6tnjKOm4DKlTVNXW95dK7JLIJMlVYmwhQ6qXixo7LuRT+WTO2bHnLfneJcvvUK2xsS69XOKWYFgO/oEtlbFuoaCuedkd7BdIqPvTt43AjvAFAwIiZnFPDnNH5ggCbWvaOlHLBeMHUEXqHDDQB7obcqmYxUFAUMAXJKa+apvFNKZMrCGCWRaRic85V3pWEFkRIbASyXEZEZGvEpGu7GCMHX4/q0cTdf/t8ca4u7JGXeqyz/ap2dd+eF0fORj46RBAR2vhjxUwVU1YSEGDdbMIdF0PhGlz29ka/Ws9eVVXFgGPmrBJjhFLpAnHDd2jDHXA7iwoXVRlK8FsJ0ykEXWD29eLS2lAuWPqW8grGXIZEzsNG3ysDKM0dwJI9C0k52FoQh77vXY3DMIxn42KXMXPX9XVdZ9+cnS32p1ORC7MaALp0IYuDDwCQs1gpZqzqQ13gRlPwtc9ZE6ILqApMNAxaVZQzmEFNIKJl95fXK3uoIk8EOZsisHNq5hypAljeIqZZxbk1SMZubWYiYpl6Vxyqbkm6p1GcJac+CSs2q76r0DETkIhGEHJQMTQEdXAnKASOMVEnIEZGZOwwpTYux43fm433CFOMJupcs920m/3JkiWmFCP1MStYn2Lbdk3l90fjpq6///7Tk/M5JJnN3O3Dg/29cfA49C27EJMQsYAMKWfNhoZkCmIGKIbIQE4xI9oouAR5ywu24aUAIOxwXTnObWQXAfz/qnrTJ82vLC3snLv+1nfNpSqrSlJr6RFqYKZhYALwDA4Iw5gAEw5MhL/Y/x+OMI5w2APBYoNZhmFWT0+L1t4qVeWe7/bb7nquP9w3U3J9UEilKqky33vvOec5zwLR9wj5UUAOoHM9ixZCJMS8zEREkXPoAiZZAAACcs5ijNbaXIvo8RnKCoLgj2CI96N//FfAMGbeDCIAf8Ivk3fHxwtA8B9M34OPLKaUI0VTdBAQMSBP/Z4jJgOlzMfZA0vgprWMry7qaRpstJzzEEPbtn3fJ5601kLkSzmGEFBwrbUBZb1jLHgeM8CgNE8qWWswHo9LSEEEkbuKgDodfdGPMoS8HZqiY0IwRpmvQZAYA++9QJ2paLncP67mQXKdhzWKAMQpgY8Qo2BixRiIHNXFWXIQWXRoeYCM2mbIIUDkQAgosGAaUQBXAUY3jNZOwQcSWPlgt5vx9m5aLer1qtEVUnC5zfLkKR6nqAzmU6gmZ40zKcXlcnZ6emqn8Ytvvt52gMBmbTOfN3V24wFiEiBiCIHIOx8j5E8L4DEy/SnBkjHGOQgGrigAj7qNdHzvARF0CMC/j1xPCBntDrLIJL9HikE6/lUmBEiA8anhSQgMePJPs2xKibMkheCc54X7sfVCSHmBRiljHZAgQY7xfowEzQPVDwCT4/1h8anci6pdPAGhKR23w0JITBUiDt6LeNzrSF0R0W7op2BSAmTFzd39MAzvvltONmF0yKQPwTmX32cA6AdblAoSScaxkMCZcy6GcZqmptD5Jmots6bMswQANsW8lX5qBjjnQnDvgXMWAmVkKFCECNbbuoSQQoSjc3sMx8o+pSNNJKWkH2sKMADUjHTCCDCkqNBLCD6F6GNE4ChZSpgoBQooBGPAQTOITDitqCh4U5Z9H6yhbkq6KJQshrH74qvrL7/2Z2erixfn/f0uqxry+53BeSIIdozRV7Wez1sh2Waz2ewO+9F3B396sjw5Xa5XdVEySs6HiJjIsxgTPBbSRJAg5oDKlCgljEBEBEAsIQOoyeYB6PGNzOxBjPK4hnhqdwgAElAAguMBzaxDQkgpMZFjuOApmi7/Lh4T4bExSHBkDnDGQR0P1g97MwDIiNDx2H3fuB0DSJ4aNnzaejy2WCkl/MWdxeMcx45krtyyHANugfPM+oFMaS4KhgjGQEpQVeA9eA9FAc5GznkiIEpCIGPHL7WS4H0Gd467FkAyxgBh3qezR+pe7i3UcePwfRua+/TkHWPMHUOfjj/vvUfwec5NKTnnjMvrXTW5TgjhnMvEKiLKt0VIhKQZA6EBcDlNJ0MvrfdD9FJKJjmmmFLMgluel2/BEUXGQXAFKLxP3lEf+r6z1hBC6R3t9/tx7ImoKIr8hWTqU+6+hBBSmLap27oEoGmyu26833Xb/WE9X756cXp2Nit0AozWeOc8ZzL384yJQClPJxShrCumefAwjhYAmlpVZWxaXCwLz4+vY378fnAI/OOhZHlmOlaSlOlMDIDR98o4Svj9KElwxAoBIAB/etjo8WABwFFX9ANg5PhrfmgTAj9AV47Li7zx+34Affq9ACC4GYgoZroI+/45nVXSOaeUOhpWFYVzTkrZdwSIq6qKMQ6boa5rWUhrbcEYRc8YU6UCgGEYUghlUUwmaa0V1yFQCEEpIQRIoZ7qbAiJccmFyo8jRnqC3OC4nKUQYyoU59wxhPg9ROwROZvD8apBkg6EBUQodDXWQgjJveMuD+OCeURM8T4m4ogMhY/gPUtMcoXMxggZt0eWRGIQIaUYGQsAEAPzDh0S54GLpHUSBZ3M2xClsykGThetc26yZn9w3vtMA4gUEFHJoijkYiEkFzF5M7iH7WHXTzHy5eLswx8tF8u21Oi9D85bF30WurDoIlEMzoVEyBiTilesfAS3H+dWBiwRT2my3w8KkNjTlJlLVkqQo7oTAEAGZYgQsofY4/kgAKTwPX78hFo8HTg8yp6OdZ8oj7757/M0/HgrGDz+fDy+I0hEiYOCnH8NiYgSYYSUEnDOn26GAG+BKAYXQshCFsBERFvLsyym6zrG2GKxIKKmabRSUsq333ymlGrbdtqPm2lKKXEhM3/iEb6icRzvjIkxrtfr2WwmkU1DD5P0jCVC5Ee1GgJIIeiRyZFEccR4OctmKXnL42NQnAuh4DGIRSAyRkxiXp9KxnQhK3WEJCacI+cKQPwgOAgRRXovBEIRicftHr3TNiWPVkTx/XjAGEtIiQhIpsS5ACWdo2m0lIyQSSpUonKOYhyD9wBJCCzmfMn52bM1EVGE3E0SUT5D3k3jNIyT6we/2/XjYE5PTz/66MO2HSVL1lozTt5TJEZJYkqRUwwESeSNQRZycAQbEmJuRGLeGiIQw7QU4YcHKNOIUkqW6fw+PbZxj4QbKTOgHnNKZiJEkZCeePoAEOH4FqaUBMTHt/QHADYREfFM3EkxpcTZkd4VE+W8zfwMc4EMchwMISIBpgQBWMIkABMyjt/j0OJ+c5dDIfNcpoRiHIHQJ6XqpZSSF7OUElcqhTAF5iiYXU8opSgu77bjOBLRYrGQXCRg1ntjTFmWdV1iJDNO3A+HbZj6neBqGAauNGdCSkkpElFVVYwxB9B1XVmWTdMMbgePm6SnzpIxdrjdpKbJQ3TeDXHOk3Ml8ymliAmeygJDAOCFQDzSVPMK6wjbxpoABZcRBVJMETgDJsl7wTLwDIxSCjkuBiBC3g4EppJMaD03IUwOSoHIQGnVzHQMbhx775PWpbFbzvOfEBhPgcg7Y5xzNsXE77fjZtuVZfmjD1+ertpSjiyBnUwIFAOjCACILBJkSjRwhlJqxoALVJorzaeBkHFEjHQsoxyZZMxEmR/IxyLDEiZKJKLNV43lM/i43Mqu+ikhJJZSzC8lIqJgdFSZHosyMUgp8XRcgKWMJQPPQ4zxowDJOY8UiYjDkTQzWELOAQiJOCaRBGNARBADIieERMgg0aPSD+L3YJPwiaQUUspIPiXyQClE59xck1SSyBUyL29cpUSMcbufQgjz+Xzq98n7ZVvd3NxUat00epomHv2skEoyMlPB0/uvno926WwgSlUzl/UyIbPGRQBjdjFGECKE0HXd3d3d6enpe3Vtuu0RU/jBieScR+49czGh8xDjMcDGWlv7GZcy95fee4IjfUlRTABCKQYQreWcH9nUakAiHjWR4BOISXEukMPh0R8IEqSElCjziShIT4aYZwJVJZKT7oDD4KMahQQTAk5Rc63UKgY29kFyDgT+sQkBwOiYN+A9TC4Yk3TVnj47OT2p2zJW0nqvgwcAoZRC9AQEHHx0RDyGRBiJSClRSFEUqqzkfnCP6y2GCIyhEFwJmBXfE1wQ+WMZ5cZxAEAgBsg4CATBGWMYpsOxzmahHcNMs6N01M6H7wdkBgyHkNkw3+tP8hmd6foplSzTQY4r6MgFsgQxpAiUOAVMGGMsNM9vMFGiBCkFQI6IPgRK2bWGicXJs7quyIehP1AirWsmRY0sOg9K9odDUSqghJg8YsK0XlfDMOSCHmNkDK2de+8shSQYT1JKYaxlCRAxypR8is6HEHqiZj4fhh4xOR+bSjvnSi14pRez+vn5yTiOY78vy1Jrvd/vQ3DGmKaqirom8rOigBil1NM0hRCMMdn/uDcTS15rjSxRConQ+TAMQySvtV4sFm4y0zRprblxRVFc3x/OdQXi4e0oOnjPKou4xTivZZxs8DFR4gg8QWIYOMMIgEIjSTIROS85Z2Xk5CeH1kBKDBhnDAU3HBICjcSRIqNMx0EfaPLRBNx1iUFsm2KxKNYL0ZSJIw+eGWsBWYze+5gIOOcUgAKDyBIFrhMyzDqYNOzfe7fc9zAcEhfCkFECAyVGrBXgAThnuWk8ekQQMAaFAilZjIwoCslSijEFoSWjGjkbhkFIxYQwxjBUiVIt0+SssaYoqu3moAodAtV1DXYvpSqKoh8OQKldzHLVci4IDkoKE61qVEwpRIoxFQqUUp7A2pQAUAjvvY9BgcQEWkoKMcbIlQhEMZFqeQgQA7oQheTgp3HsO2NMURTkzWE/7Q77Qunlcqk4RGuNHVNKOguZ4WjFG2Mchn6/30/TdHFxMXTdcrlkZRkjMcbLshyGYbvdzeczAJicQyF2ux1BUrJQio9DX1WVFEWe3awx0+gg8S5Z1o9VVS3n83EcWIIIiFzmevbw8MY5xzk/PT0lCg8PNzHGaZqIyPuYZbhd152enoqiBYDonFJyPp9JqfpD1x/2p+ul8oECAhccIC/OEBlAZIwJpJCQjnQUJDpiG7kxhxgRkxCsaSq3tYnIPuIGRIQUIREvVAqRQk5eZTGRixRi1FwVpZ7N1GJWVKXiPKVIMZL3WRaVW49HDWFK2dgjU58xd5GoOBerpegPk7WaAJyNKFWlNUfw1iDnWggi8pPnnGNK0zSVdRuMjzFKyaMJOW5xPAxalQxQSyWlTIiBMc4ZY8yygEWlVYGMtc90UWhrvPd+dXLOIBGRLhpERK4JwPoUIjIhQgTgErgM1hNwF2xRFJ4i47xsm4yKMC5mVdUNPUdmfGSMJZ6sHY8NARMhEIDgQoqp65xzh91mmsamadbrk7aumqqs63oahpRiIuIA292uB1qtViGCc3YcRwCYzWZaa11Iqfju0B8OB875crmy1t5c30kpn7+4uL256vteaqVT+ebN5Xq9Zii+/PLLF89fMkf9uFdKzWazdr5erM6qqhqD6/seiA6DMca2bSu4sNYCJqnkYrXknAdvGYcQg5boCar57OHhAaOzoyuK4uXz9WZz34pzzvkwTojYD4exHx4eHrbb7Y9+5VdaRKH45MWYonOukEIUnLzlAjlhcBkJwUScMmj6iJh4isG4TAxr2zoE0j5kYQARUYhEZMYJgAVigZIPMVEWuKVZC7OZXi4aXQgOiVIIgbwPmWIMAFJKzkTeUMP3OB/LTpcJAJF5D+0MkDkKTAiVkqfInLOb7YGMybO2977rupRS9hTZ3D/kJi8ntiCmVFXBe/BxmiYhRNRqmqyUUih1c3VLIc3n86qqhnGIMfbQIeJkzb21bds2ZaVVEWPsByMkZ4CTcT5S9CFFXxZ1SFTVjS6EcaMxBhFVUSilq0YTwTBMVVW1tbQWICUpMURgDHxMHDGEFAmIEv7Lf//72b8ekKSUnMmER5VqcJ5zPBwO7axuyoooEtFgptyc9X0vhEgQm6YBAJ64McZ4t1gsGZfWemNM3Ta7zQMAWGvPzs7quj4cDl3X1XWNKDPMlFvAGGMeenRdpJTsNBFRSlFrLRifpqluysNhH30QDOq6tJMJ0UXnhVDGmK7bLxYLY8bD4TCfz7uuQ1mcnZ0xxrx1u93ucDg0TdPWJa+amUBgxTeHYmsaN0xaMeJFoUIitB4m412AzLlOKXFwuU9CSCEE5wwACCEUV4FSCBRDiglioBhTijSOY0ThiQ3WOecYpLaSVSlPF6qqCq0lIHnvgyfngvee4lFh90jgJcqSYkMZkUBEpQUACZbOn61PXsgvv+i7A0OpGKeZpOdzM9P3jFhWIZZl6b3f7XYhhKIoOBePkCdTSllrr66u9vv9+cX5YrGYz+fjYO7v76WUVVWN41iLoq5rRBzMBECMsWyUjKqMMXZd99RNlpUGAOOCYCAYJ6KyLL2PkZKnOGvKzWaz3e8Ph95au1gt1+s1IjZ1K6W8u7vLf55hGPKOo2lmKSWpy6Io8BdvN0IIJIp0dHJyMaaUttutN7ZtG0Ssm9I5Z6dRaz0OXdM08/nMGDOOYwhhsZxZa/3khVbeB61K5CwE2u4OjDGG8ezszBgzTdN6vTbGEFHbtsAw/xfySjqlVBRF13UU4nw+j+SbpuHIHh4eyrKo6/q7Nzda6+VyXmhZ6cKYKVFwzh26QQjRNE0/HKSUQrDb29umabx1ADBNU1GqUmX9UBjHsWpn0fSWqttwHvkCXdRak2QCHQIPPg3GWxcJWN7/JLLs2NpjSikEDykxBoiJCIggBgqBnE/ehRAIQU7OD8ZNPjDG5rVeL+tZU85rwkfzCR8oxuR9dM4hMCllXk7So56ViCZPjDFMgCxVWgnJiYLW+t0ft9sH9uZqdIRVqRcanrf9y9MeqDTG9H0vpWyaZhxHY0xd10ApX1TnXO6tD4eDMebs2Xld1yGEaRo55yGE7nCIMZ68fF7XdYxRSum9HczEOS+KQkeBiOM45jVVCCHrCh+2e6n4ar5w1jDk1rtAUFVN1+2HYdBaV1VjrXXOAcMQaL/fOuceHh5Wq9V8Pj8cDplxsV6fZu8qXRRis90rpeQRfkFj7GRcjPHy6mY5X7i8eofUVjWr2TRNALDdbr33Wuvc+SJwhuL67lKqAgDqOngf9/s9Ebx8+XK5bB8eHvLwe39/P5nh/PTMTIOu6qf1TP5Ucr6pZFgURd/3u83GObe5uy/LsmkrrWvn3Nu3V6vFfFBToVTe0DSLFREVbaPqKgOfZ6JomibZ0VrrrY3RD8PgnMnmG+CjMX1Uc13MLXI3Tcxy4shyjA2i4ixgjJQoETDGmYoxhhB5QpEt+fN+IkX26GaQe05P0VE0k/Pe+xBLJeezcjGv60pIQd67rEqglMFnBjxxqSDS99KFcMQaY4whRp4kA645k4oJmXwUxof9btB6zgWSCYgFAgvRAVHf903TZFZRPpf5E33Y3t/c3GTs+fb29vz8/PzZWT4ll2+3y+VyPpv1/SF5N6srzrkCCmO/2+0y4TI5S4wFIttPRVEgJGPMOBgAYBRkoYObtveHuzffSSmfPXsmhXLOPAzdvJ1ZSIfN9u7qOi+6yrJGgHlZ8lnblkVRFPP5/Gy1zD1PNAZjRIEURvyDz15LKSTjjAMRTaO1wXMuovMpJWMmrbVUXDDOGAghOB6pikRH59mu65RSTBZt3eSdXi5DwzBUVcU5xhjHqacQc6We1TVjzAGXUmYvTGPMMAzOubIsGSTnXN2UwzAAZQarEEKMk8v/x7ZtnXPeOmOMlJJLke3REPg4jlLK+Xx+c3PTP1zFGE9OTqqq6LrOmtE5Z8y0mK0oDaz5cAvv9NaEfafVzClXJHEkYhKM1vWTi8SAMQacgieiHETC8Yg/52KdcXIXonHR2Oh87KdJC9FUajEr57Oq1CylGMkTUfA5K0ikhJ5iImCM5eaRYjryBI8/0EJA4hzZrFF1KwCjjxADL8p0cnLy5sb1ZqqKeiahoe9WzS0Fnb8P0zSllKqqyv8IiXddpwullOq6fW4SLi/fFEV1dXV1fn5+fn7u7cQ5z4zBWVHsdrvPP//SOHdx8bIsy9lsFgki2byDcc5xJhPD29vbm5sbpcvT09O6Kuq6BoCbmzupdEppGIbVYpndA4xxZVmWZQkAVVVJrSZr86PLGOsPh7ub208//0opMZ+3TVvh52/vKETvbVYS+hiIgAlel5UQ4uHhgUHy3jMOSikhuJliNtoyZqzrWin19ddfC8mkbueL1hgTH2WQ0YfZbFZU+u722ns/n8/vb26stcvlcrFYzNfPp2nqui7GuFqtvPfX19dVVTGBl5eXH374ofd2GAbBOCLO5s3t9bVzLiYCgIuLi6ZpvPe3t7dNVe92O+/DYrGQUt5c31lr1+s1+mm32y2WM8R02O3LSjdNo5RMEZEZI9775XY2+qFBXhb1vdnpqLjIwgMYbTgMxvmEnAcXU0r56OQ5GFMkouCypQLFkHwk48LkgvVRKDmvy5N5MauFEglZbgSQ0lGCnBJa43LNkVIKhs65GLJQi+dziYgkMbrEka2XdVGB82MgDklxns7OVlcPoZtGJeSykKX/WtNXLBV937OjYhAWi0VRFPv93kT+6tUrYybGWILY94fZbMY5Dp1p25ZzbswoGOu6br/fnp2d9cZWbbPZ7F6/fi24OvT96ekpIk7b+9EY76MxZraYr1ent7e3V1dXqq7eefkKic7OzhDxm29+uVid9OPw4QfvNU2brX6i89l5mTGmlBjMJJQsiiK3DWM/kA+z5cVutzF24jzhf/yTP10vVykdB5eHh81mu//gow8VEzFG5KIsSwC6vblqCqUEU2VrrZVSMsYmZ5ummaYpJlJ4hIGyjI0hsuyrxo98XudNniudM23bTr239mh1WbezvHfZbQ9n56uqbfKN9OHIiQRgHBlism4ax2G/3y8Wi7ad1XUthIghGWe11kqpQz9k56NCMiY4Y4xC9MYEPymeCqW6ftsn6fnHt511nobtdHZeUtATWa1ENvGIgW0O47ZzCTX3lhBiSCE6xpiUKBgCxT7YlFj00tlkjKPohQBdiEXlZrNZbogTRAZHf82YIFNirXMhHA0QuZIQAxE4F6wJgSC/ZAlBCJXIFIovFzNMrOtHogAsNfW6OkFn1OaKWIW6sR8s3Et15VE/PDwYY1arVQIaxzHPK5vdLtdxpXRZlpzzvDMPHpqm6bp9CGHWVFdXV1dXV4vF4tNffN513Xq9/smf/3POufViOU3T27dvZ4vVF1980TSNm1wI4eOPP3YuFEVRVvKP/uiPvvvuu/fffw+AOeeeP3vx7rs/0jo3yrjdH5RSwACQ+v5QV3NEFEykGAFg3w1FVQKA4ERPspaff/0dIAXnrLXZpKVuW865FoVxXmrlnLu8vKzLQvAjgYRzDohSqlzHPUVrrXM226MZY4J1bds2TfNo0SsAUtbsUgqPim+fUhrHMTEeY9Ra58xrJQqlFCCvqkpr7SNlCGYajFLCOaMLmVLabDbnZ88zH6eqqswQY+J73jFH2HeHbCh3e3O13241ZxxTDBNWS1I/uemGYTTo+fmzKnrVe8MgMYiCccbVaOL9bjj0EwMthABkLpC1loJLiRByzgzlL4UjSMXqSpWlPl9VeTh1zgTnE+TVISJIIor0A9o8F4iIKUDClNDHvEk+NgWUvJJ48ew0OD9N1jrvvb9453nyoFbAsenvYQyjbvGjE/ZK3gShMjk/czWstd5bKWWeuJ1zmWqUYZq6bomCfVx0pRRDCM45Y0yg1DTNfrtTSuSK3O33q9XKRffpp58uFosXL15IxsdxHMdRa73dPnRdp7UuSh0D9X3//PmLk5Mz59zN9V1RN3VdE5HzvmmrGCNiCs7HGCmERNiNQ9M0uizMOBRFkWEsUbcNIpppIKL99mEaWNu2QMQE5zEQ0Zs3b4wx77//Xtd1fX8oUUgpnXPBu2zeWlWV4nyUXBzpysCbWnGx2TzEGKVURaFzl5NnTyLabO/rWX1ycrJYn0gph9EYY2LfKyGcCVIrKY65T4iBMcYEE4INw1AUarfbZZzCWtu2bYwxP8/GGHi0S8joUtu202QPh21ZNSfrsxjcNI3Xr7+RmgUfBVcpWWDcehdt4pKnGDKBBYHqUsUYKZhuJDeZQAAoCSVxnkIkIgxAKSB6rXihsaxEVSgp+Wa/O+qwEDkcJUScM0gYY2bjp0wPIx+JCFlE4IwJAIgBrPdHW1CN8/l8MBN5cgSBWNHMxymQtVDrsgQuiPxUqiVHNkzccS+EYAm77Z4xVhSVDcRk2Q+TlKooC8aElHIO4JwLIZyfnd3d3YUQQkzTZJummS9X+/2+LBrnLC65lLLQGoCEUCFGH93JyWqxWMxmjfd+2vSzeVsUxWLZDsOQUhzHUSm1PlkpqZ0bUcjzi3PnwjRNXIhpmqy180Xr3eCcIyLFBZdMaVCaFZoHA8GZ3ltExD/66jXDNHYHhMQwTdNUluVqefLlZ5/rqizL6ouvvjw9PT09OztOZJHquszIYlmWxpjsiyCUNMbM522eWrRUMcb8gGcQIU85WmulxH6/T6nMIIWn+OLFi9xhMMaCG6SUXddl7z+ttSx0jBEpOefevn1bFIWUMos8pmmq2obD0bdjnHprrWB8Pp9zXQDg3d1dPw5t26aUuq4TjF+cnR08PnSnU8LNbstBLxYg+cylmCIJRgwwxsC5YExMxj10vuuHrjc+Mko8hpQtKGqtOSOlU1FAqVnOPU4pBX+kRPAfeMuklKJLIQQXiJ4sPxOklBjPJB2MMT2tj6XkZ+drwdN2tynKijNtTahm9Tj2J+2czZjgOozGp7GdreZIS3gzRpPbg/2+Y4yt1+vs/Qfks90SEQmh8gcXY6T0KEVIiTEWKFprrbVaFFkYIxjkjlAInlKSKjPhA2csb4DbtvXepaNd7VGMVpbVOBqtykCx6zpjjLWeocgAkHOu624zwqC15pw75ziXmVmWb4sQAn/v89elVkBx7HdD3799+3aapvfff79RMqWUy/dqtdod+v1+/+ziueZHeVvX7R9jJZLW+rDrlBYxRmPMrG7u7m4+/fTT+Xz+q3/511NKWutcRDjn4zh2Xfejlx91w9D3fYzxxYsXXB7t1iE5zvnhcPDel2VZFQVjbJqmGH1ZlofDoW3nuaMFoOzOhYhKqez3IBjPEF3RtPnVRETvI3LGOacInKuDh+vtMnJ+v3mQTNd1FHKeJXmKC4bJWgvHKE9ubBiMHUY7mjBOztmsu9BliVLyUjOlgTMEwOQTEcTEAMB7b62NCYQQCDzGGLzNHLCUnjyws7QopIQhBO+O+X9VXdZ1XVXV28tv67osy9o4wgjIoKxkq1pfJGCyQFM35JxIw+H9UyMKlXUX3vuuG4qiWCwWXdet5s0T6dh7v9/vY4xt2+Zuqu/7cbJHKx5k8/l8v83bjVJywTkCUlEUw6Er6jJbmUrFs0DHW4OIVT2nFB5Bg9Q2c+d8WZa/fPNNjLFpmrZtpzH3DwwpIaMn3OrJhWWaJmPGDIrFGEVZNdPYF0pWzaqZrZ6/fG+arFKKbO+myTs/m81SSmfrk5OTk7ptvA/ee84ZGusoMkRnfUhw8fLVbrcLcUTgm/1u1/WEbN93r1+/Vkqt1+tH3zVBBFLq766+VkrF5KXmt/ffSq1SSnVdmyGWpS6Komkazrn3nhEJwRbzOeeCM/izn/08Q2Jt2+pChuCyPT1jTHCFCl3wMdHhcGiqKkWfCRxSamAsBHJJJl2ltLDeee+5lITgfWQ8AlKMER6NYvIV4kiVYkrottEpzb7nhqHL8tR0TK/loFhKfHL2+GSGQAQMRZb+5iYEGCIcRRoREiBEQkrkI3mKTPCqLtu2LQp1d3tPkTFR+JjIh6qqErlxOHz185+fvPfu81evlIDTVdV3MHoBMh12+5SSLuRi3nIGSsnTk7kUaezH/JJlJryUgigOQ7/ZbIqirKqqaRopNUFKhAzFan3iQ5RSScmVUkqJQkvn3DhYOS+01gkgeIPIrUtNU1/dbACgrsuU0mw2G03cbA5XV5/NlmVRFONgMhDmvWeMP3/+vDtMjPNh7A7DQESF0nm0iOS01lXVKqVE0yzKsi4LlULs+x44m5cLF/w0GVHMQLhdNx52+2bWqkIbn5jQjMnEeLs4d2YMIbjR77v+0MfFYtaunjFMIYRytn7+zgeLxcKM0+Nz5bM/6lk155xT8gCQR6uYAiJmgG39fJEN3Lz3zhjjiXPOmHp9ecm5/JM//tO3b68uLi4iildKf3d1HdwYY3rnnXea+dqFOLpAolydPjfjNBy6/W6TUuSI++6GAE9PzkUlA5GPznofgguoAHgCYCkpzkNKMUZECQg+xEBeZre3lDhwLpALlmIMwSMjBIwhhkAxEh5jyLAqCiLigLl1oQh5OX6kxxKkFD09DjMEPhIkFmNKxKTUyJWz3hizPQyLRRNjMsYoLrw1N5fffPnVL6b+7gX0p+dnXMZSgkUQTE/2odSFMSYFmIbRTpN302szbjb3J+vnQghrbddti0Lnqz6O46xu8kOVInnwMcZ+mLquOzs7XywWXXfY7B5mTYuYlBYnJyfb7RZZ6rpuGAYAEMiMcd7vPaEQIgD4EOx2G0PiXMiiaurlNA1ScqHUNIzz+YJzfnNzo+VMKlXUTc3nKaWqLjiy6MMwjYfD4er6YRxH/PR6lFKmePQJNs4rXXjvC62id4KBmYblbGa8s9auT06GiQBg6gddyHEcGSRkaRiGer6IMZZKKqXGaeAcm6axkwlmaprGmOMGOQR6tP4vrZuykzmTLGstYow++rquQ3BAKRPSpn64v7+/v/02JTTGLebr1Wqltd7vd1JxsnY009nZs7JumRCiKKfRIhfBTJv7O4o+hbA/bBmK1elJUZQhwUho47u8ZONIw8EmHIxhi5lQsnAxWnOkRIQQOCRMjAkOAMY7iIELVJIxwBACIk8EIebXEoiCp5h8Hi4TZwK4CJ6mabLW5wxOOsLtKRMTAYASfzIIqMuqKJTzpt/vynqeIK5Ws/1hV2k1Hrb/x//+v97dvPlrf+NDqp79V7/13354MXvnov7qi9GM08XZ/t2zF123R5asnQCSkOzu7u7+/vbliw+Wy2WmGcToj4xaSCG6RHh/f9+N43J10rbznOZU1LUdJ0SgFIwxkrOiVN57xlJVVRxzpozc7Xal0vP5/OAysXWSUt7f3wOwqqpDCPvNfr1e1pVWSoxTjwlCCIIrSqJumwhJKZn9jIIz3jqpynEc8w4F/8u1yS8T45jRQaUUUeDI8jyV25TvwyIEM8ZkKbsxxlrrvZ/NZrNm7pwzZhzHsSzL9ckSEZ1z+LjPtdbmdRPn3FpbzirBjqt9Igou6zGwbea5tzgiSkjOOeeckphF3Ll3xEeTN8a5kJwjC8EJzvebB++9EOz05GQcRztOSinnjFIqg1lDuth0fbWYVTOJkSQyM9n9frh+KISKwD0Bw1RFlyB5XbDJuNyTCSFdoGmyMQATUjx6tDImEsPgj98NZwvnDWPU1LkbtuNgicAfk5nT9zlRwACA2ICIjHHOpZKFYDIEcs4JRmcn6xQdoLu7v/4X/+Kfq0olAJqXF83ipx9+/Ft/56fFSn39C197t27+bDW7IILcrnIuGEPGGONAISaE/X6fWbDn5+cZtmMonXOJoeAqtxPAOBEFZ5ElyaEolDEGkbuQEjCMpLV8uL+h5GazWQwpulSWleMaEfPC2U4mUhCCeW+RKa0EADk7IWJMNI22rKubq1sfaLVaoRDROSW5tyZ6S0LlFVQiFH3f39/fK6Xmi1kuoG1bx8g4sqrS0+RCCIvFgjGWl3ha8qqq8gHKAGHGxgSTKSUp2/l8jogxpEhOKWWtyR+e0IqIgDPgTGjlXOjNQHT0M7bWZkfMZraUUnKKEdJojcxfblU5M/oQEVGqQgJkBo1SCjFtt1spRF1X++3u9/7gD+9vbpfL+Wq1+uijjxazeYxxuZ4niHacEFHyzTD0BG2pIbEUcSyrUipdn6TLt91+h4iCSVdoFFxTgLo8upYd2WtZNBFdZxwRBUqQsn4XPUWKDGAoKqa1YgysnWwYiUVAlihlWjtiYseMAUTgDGdZHI7AmEKpUCqutKi1jGmcLZqbq82/+4//AaSMoJjg69V5rapt1xGp19/sBavqGp3BLT3EkBIywVVRFFLlqOrQlFU2d10ulxk+A4CyLIEIIdrRjeEgpJzNZlIKY0xA4oCMMY4MKLnorI+ILHjSZTlbnex2W+MxBYpECkGVxTRNmWrJBK+KavNwd39/27ZzaCopmB2nuq66fnj+4kIKPWvau7s74+ys0rpdAEVsCvL++n4jqlLrgnOJ3x7Sbtfd3t5ywZRSOY1eKcGRLZfLbI8xn8/ZowVRXjnkxxIAMiTkvddcFIWQErrOZbpGRijaWXUE51LKWplMx/Ih9H0vOG/bFh+dMASyfhrZ0csqWWszSyOEIPn/z+QzPpqrZ+RICJYiKS3GfjDGWGsy6FDX9TAM3thh7Nq2retaVmG7L/ZdHYGfnKi25dYFQkWwl3x+cwNXV4eEUcgkhKjr2lufHzgAiIlCiM4G7/3oIMbobLAhxsdAekpYKKd1yZk0PvTdYJzNoSoIR/NSePyBR3pj7b1N5LTidaOrQnKRgGKhMFf53/3d3/369Xez+WI0VhWVbMRZuz48XP2Dv//3imK+nquzmVnpOE4P2QMjxhx4fcRoggm5Qc98yvzZEdG8rvJrQkhZrZo/Ta4rjslOow/WOTdrF1IXiTAwfn19Xagyf1cZA8Gx6w77fjw9PUfE4ClBxATTNAASR1aWxeV3bwBptTwBgH6a/tN/+k+Hw365XDVNc3p+VuoCEVbzBeOQCPOdiZDE4TBUVXV6euq8zbhR13WIZTdOmZ9XFEXGq4UQm80mc3P6vkfEk5OT9XrtnLu5udltNkVR5PZFCJYcZL7q5dXtkUods9xE5SSUtm28z46dYMYxj7qZ1ZZStp4iIY7qd8ZYIih0xR6957RSeTOpyzrG6J0fx6mBqmmXi6UwxhCk+/v7OExKFSFCBBORM1WE0Rcq1S9518XN/S76eTVXjMUC58a782dKyObrr+5j0GqpH/Y3BZtxjll4zFjSUkrOvWeyYDGmEIJ13rkQPMWYEgFiZafkrDcuuiAisQQeIGGSPzAE+F69H1OHiYREqVCwBBgQgEuUslSIf/rzP/v27dV8sUxc+GQlZ21TqaIw0f7+H/3ZX//13yL3YM1uP82YyJJvHhPlenI0BppBHnSIKCWq69qOUy7lPoSIiQvmQhx32wgpxsgnR8FF76q6KJVOEG+vr+43WxvD8+cvrZ12m+2rV6+2u7vN9m67fSiKqi7UOE7GmGfPnu0Pe631arXY77o3r3/55edfvHx5URUlY6wpy5/+9KdDtzsScB+doK2bUoqFKqXgbVMBAP7xL3fZejVEH2PMN8baadbMOQfnIjxaEDHG7u/vu25/dnYGAF999VWM8YMPPqjrepqm3WbzuLNKUsq8oQKA/X7/1FNm0KdpmvxG5LBVABi6PqWU/9eIuNvtjouZunj6yXEcnwyf4OjQkqcNRMRsAcAYC9bmST8CFIV2zhVFUVUiWDh0u6qqZFRTHBxaqasUi9ff3vWT+eDHrzjB5KayksDFd9+Zy8suAZOFZBGFZAAUY0gQjxTXCPkpgpSxaArxmE6xP7hhMMPoIglEHlMgIGSJf58R8EQFysw3KwXTWhdKcM45AudcCR5JXV1d/d7v/2cPYTSDrjQyNl/MJPNKt5PrVNL/6Lf/4QevzLI9dHeiKDGEaH1kTJR1U1UVIPpggXKgSeScT2Of20etdTtb5PQPIQQg+RAmM07TBIGklIUSguHt7e00TZzzum3KUgOwu9utELKp6v/8+78LGOq6VKp4/vz5s/OLvh8Xi8WbN6+VUmfnJz7A3d0dPpqov379Zrletc0cWUTEpmmypUDf99b6tm2Ds5lUKoTAz27dNE3DMPRDV9f1er2OMU7TED1xzjebTYzx+fPns9ksf085x+yKeXNzwzk/OzvL1YFj0rokooeHB8bY2dmZVkUIMfMYMj8t08vzkKRKlZvIEMI0TYhY6oJzXtbi7m6f59+8K7J2AgClih+UvO/lmEQUY/TeZ9bmrK3btjXGJGBVVTnnGINEVBTFMXoIuCNKHCZziMFKWdzdhzdvDu/+aHF2dm5dYpyqGf/yq+1XX2/Xi/cCdZwjshRjAPqBYWycCOHRjufoyofAE8JorXcpJQyRnHOeIiIGazM17nH+fXQBYSknnxIlChEegfXtdvjjP/7jq/ubotLG9lyJupR1XW5v3p68eMHKclXM//7f/I13TkcppuXsXQouxugjJmQIjCDZ4L13dXl0z9NSGGNicESktU5MPpEMCSATdvq+VwI4Y9GHFMI4DDH6q5vrq6urv/AXfrLf7qTUL1++ZIw93N0sl/PLyzf/+l//31rr//4f/eMQaBiG+/t7zvHi4kIXTQhBCvbwcJdvQt02s9kCEe/v71M80rpVUXbDxDlvCm2M6Yaec45/+t2R4O6Dy/uocRyLQnEUKaXD4TCO43w+z5iCUsrH4xnKgXmPDxWP1nsfn762abSIOJ/PcwI1PFpb599FRCgwhJDl2/gYPyq5+Pa7N4j48uXLJ5YAANR1nS2E4NF9Jq9MQgjDMDnncuv5tE/bbrdc6qpQy+VSaz1Nk+SiKFVKCWIMwCIkTKGUjELseo+itslFx2MEJpiuJOP86sZ8++1dPZszxhATAzo63iQEAO9sprXQkxSVIUCOk0/52njvnY3eRSLApxShYxrL4+nMnJ0QcrYIFyql5Jy7unvz2RefU0rOuaJU09BrxY0d06E/+dGLLvB3Tp/9lV9p12qIns5fvbOet5xJWRRcqEBpsjalxARfzJac82AdIKUYCqWtm4wxxvqiKHL4iAtea53JEIe+nzUNUPLWRO/rury/v/vld68vLl5475wZGQOttTGGAZdS3j3cP2z3P/3pX1KyIKJhGsep11rPmwWmSBQpeu8tchZCWJ+dDr3lmKSUwflhGhPyhOhskDIBQAxJCCGMMdvtdrlcLpbz/PwURYGYPdbD2dlJjCmDiPmWcynKssyaI0TMW8vDYaJosyfYbrfbbvd5PJKFriuV88HhcWQWggNw4khECaAsS6VE1vREyHSh4wq4ruu6rvu+H4YhiwH4Y0pu/mXDMJRlvV6v8141W3IbY+J2c39z8/577wmh8h+16/vNxiWIs/Yk4ADohp3hoTo7PZ21dvK3Sr/qh4mMnYa03/pm1s7nxYt35O1dhOQQE+PAAR8xHSqKCpEw59Rnr5lAKSVuhVTIMCUKkildiiDQuWAopIiUUoyZyhaO5ngpx4SFCKksddWofOWu734pixhj0oU+7PdKillTjYd9yaUzo/GVUgrR/PjDj+azZ2/v3xwOm8R46eu6mQmpdCEBgEs2TUYpSSFQCt66EEJwPkQPwQePZaGa+SyEYH3IApKqalygaJ23/v7+1ntLKdR1EyIvygYYfvb5zxHx/fc+GAZ7uN2eXTyLrPj9P/zZ8mT98uWrxBQv2oi42x2qqlCC7Q771WqRUkwsXV29bZuTXdcHZ9q2ZSgIcT5fxgSSUd/3O3MgAPyjrzf7/b4oiqapHykU6eHhTkpdFMXl5aWU8uXLl09tKceodXlMa5Ta+yClQAQia52LMXmKVVVpIYeh00rGAHlAPqJQKV1eXnrv66Zs2zbEtN1uXaCqqVPCruvmdeW9l5yFEJarOREJwY0xjKsQQi7Nq9Vqu91m5RGEaIwBJnKBSIi5r729+q6qqrZt8/nOqIK1luHR9jLrmDKxwBhzfX1trTU2Lk9OJuOKsp2sB4ZfX3YCi7paTP0kRQL0lAVkVkspheQpxXxkiWKIjnxBjz/SDxydzZSmaQqJEDFQiEebMSRSKUWE0FRacCxKKZX6nd/5nc10CM5562JwlRJmPHSHzel6HUmevvuyD8hc+ge/9au//Tc/YGSMF1KBktJaW5ZlxoNZghACMWGMYYBlWYxdn10n7GSIY6HrcXB399vPv/jGufDxTz5ZrVal8oCUGd/Whf2+A+TLkxNGwZhxNm/u7u5ub2/X67UUeprs6Px2u729vf3kk0/qutzv9y9fvnTevH37dj2fIcTXX3+hOGMc1+t1URS//PqbEEkIZX0USs+X65OT05ev3r29vsujghAC//Crh0ejlSoeHYhxGDoAJoS4u7sDgMVigY+0l7rUGcEmomx0OU3Tw8ND3ZTL5RKYCCEopaRkQMl7v9ncZ4J6ppzk4t73vTFjVTXffPNNVVXz+Xyz2Xz44Y/fvn2rpZjP53VTxhjv7+/n87nWehj6UumqqjabTW4ic6VmjB32e+fcdrP78ce/Ml8tKUI/Dp9++unrX357cXFxcXHx/Pnz/CvHcUyPaSmz2SwPHPl29X2f/ySTdbtD//4HHy4WK6ULRBg8/JdPv01RaV0DS95bLnmMJLjKLJgMrIQQUkL+GEv1hP48/ZVz6Zyz2foqAnJGBNZaM9l21iiJpRbr1eyrr7/+f/7dv7m8vATJjDFaFRnr6PpD29affPKxG60TuH7+7v5m+9f/wjv/w9/7qeTOBTlrS2stIuSVxKHbvX379tWrV009d845Z4UQwbphGLz3dV1Xc+FsGEZX17MEzMc0n8+JCHO0OkJek9bNTOviMPRtWU52FEJIyXOkD2NMqzLfvcytpBRCCJk3w6XWkkfvvv78F198+dl6uXrv/R9xzu/vrv7sz/7s7vahG3oiuHj5ztnZGee8KNk0TVVVPXv2DH/+dsglmHOWUUnGGFFomhlj4P0xxyk++j1P05A9W4dhuL6+3m73ued7dnoGnH/7y+/uHu6FEOenZx9+9H5b1ZSO2yDGWP7wmqZ2zhtvtNZmGDeb+77rLs6f5Ufl7ZvvpJTvvvvu7d1d3w9MiouLi6urq9N5wxjLblvr9Tqbb93c3Pzyl79s23nbtqfnz6qqWixXMcZhmA59/9lnn5Vl+cknn2QdQr48eZx/8eJF/qozEXO32yWk09PzEMK333774sUrqbVSBRGV9eJ/+6e/UzcnH3z4iQuRIOmiMsaNZlsUheDKWjcOzvuYI/2YyOkK7GkmS0eP8cgYE0LGgP1oQyAEDsA4c0Th7vZacLi+vvy93/vd3WG/Wq2mafju7aVQRdPMQIhnz56dnJ1Gooqz9nT15nbHIvvV98//7m9++Of/3PvjELmA2+ubrOekFDiym5trInrx7HlGczNnp5/GlGC9Xhvfl0UdExS6pLy9kwWwxFELIbwxRFSV5WSsMaZqZhScUqrvOyJiUjjnAJmUUiZMQI/XMiGiMaP33nhYLBa315f3d7dKiQye/PQv/bqddsaYrutCdMvlknP+8PDgvUcQeaqu61o8md3HxyRkxpjWZUrJuahUtto+OuDnYSI/MET0/vvvLxYL53KwMN/33Xg+NbPMGXvMZJaYIYnXr18j4mw2U0pN02S8GcdRMnxxcdHtdoKzh7vbuihLLYqiJApSiN1u2y4WWuuPf+WT4fDw8PDQj9M777wzGvvm8qosy5fvvDsaO03Tqx+9u5ivQoiT9d77fTfMZvO/9tf+xjAMb95cZmS0LOsPP1wbk1kzMI7j/f394XBYLpfr9Ro5CMGEUD/5yZ8TQsQQLi+/u7q6qs/f//b6mrHDFPD9Dz9o2/bu5q4s2rZtIbHcLpelns8L7+MwDIqzRxPGo11k/vZywabJUDSIPBFxZDn/4G539yd/9Af/5ec/P392utnc39xclXXz3ds3ZVm+evdHJycnyJn3sWoaBmC9E+U8xuicWc9ON7tu9Nib6BwVIOaLU8TEGI5DV5TFx598cn9/X1WVtfZwOPT9ULXtyclp14/XN3eMV1rViejQJSGQQR0ikqeiYPcPW85gVjfWZQIe9n1fyOJw6F2ITVtJpXxIIdGsnimgruu8dTFGrZUQgnlZ67Li0ozTcn3KpZZSBopN09w8bJGsGYeUkBK7u33IEKFzTrB2PjvNMwN+ejk+IpHf55xxjoyJJw1NejQez2+Acw7xaKP/+vXr169fr1ar9965MD5UZVPWFSK3k9nvt0CUVcOr1dK5o3npsZwp3ve9Fny72Ry225/9yR933T7F+Bd/7deqqmpmcwDmQ+BKSaGttYdup7XOuGtZlhmnNMZcXl1dX1+/9957H330K4dDv9vtmFB/+Id/+HBzXde1MeZwOLz//vuvXr3KWrM3l9/NZrO6rs/OzrLnTF3XGeXRWjLG5rPZOI5FoTOc9k//3af/6l/+29XyfBzH6N3f+q3fPFmclKq42+0zMiqlRJbyuosxNo3+hzDkUymniJzzSMF7W5ZlUag3b1//7Gc/u3y42z7cF4VaLZbOG0A+TZOuyqpaVKW+u7s1Y//s2ZngfLfbkA+qWT3s78t6dnb6an/z5n/+H//W3/7Nv3x46DLlx3vLOCjOnTdCCM5x2G5VWaSUtpt93TZalyGE+80DkL64uEgMh6E7shiFKstyNEOKxDi4yTw8PMSYFqvVYrHKZappKqlVCCGEYH1s27YqhLW27/uMNOUnk4iWq4UUahiGh93+xYuLaTLZXUdASilxzjDFaRo4AyHENAzG2cw/NMaIX/ziF1nq2jT1k3CYKDF2zGNkPwi6y1BfxvyygvbZs2cZ5QneMEClWfA2D0yllimS9/7+9sZOY+4dhZLTZAUX15dXL15cDH03n88LKT/88Ufvvvvudrslovl8vlqt7u43y9W6G4eyqIQQv/j8i7Ztnz1/1XWdkGU/DOv1WqrqR3WDXCeUQvGiqsJmM+52v/EbvzEetpvNpizL9Xqd1fjZmOGTTz7hnO92O6XU6elpFmnc3d3lqQgAAOjs7IyIrDUxxsnSvp+Kyumq/vqLN//sX/yzi9PzX/vJrz579UGM0Xvrg6WYGMumoD4XGXpMVn06moIJ77wu9Xze7vrNZz//9Muvv7i7u9l2Y11W7aKVVSGhEFK2BIAsRry8ulGSvf/Rh/1u+4svPqtL/e6rdz775s74w9nZs93DJlB62PfOR8Tkgu932/l8nijxUtVFMY6DRNUuT/b7fdd1xlmudVnNmrIG5JTcMN2PY884LhYLzgoAKEtR6hYA+r4XZVG8uLi5uf3mm2+Eusx86o8++oBS8N5XZWMnd3d13dsOEZVS5+fnWpfDMACyCOnh7p4Jbo3jUu33B2utHae6LrnUdV3byfhgi2rupsmYKHT98uxVZrSkpMV7772XNzFSijyfZs1RSpjpvRlizKm8wzBwwLIslVJt1XKBmNLpes0Y+9mf/KKs2+CjlBqR13Vdl42dBl1IpcX19fUXX25ms9mPf/xjrfWh2714fuGMy3cLEf/8r/306uqqaNrFYqGUipSevXiBiMv16nAYEPE3f/M3rbWbzcZ7v91u8+xclqoC/Vd//Scpwe3tDgDeffX8yy+/9LY7OTl59epVbhyz+nsYJsZYWVf5ojvn8pIpbz4zGK+16PshRpPh+gRw9/obsAMGM1vPGKd+7L56Pf37//B7H3/88ccff/zjH/84M7UAILN3wzHCAxjDlI6JkSklhmF9urTefPH1Z1c3l4nhYr0Y/aSrumkqKaXiop/GYXCr1UnXD91ms5y1TVNdfvf6008/Xa/Xr9778e5wcC40Tf387PT3f//nq2ULiN98+8tWqUM3EdFs1gzGHPqurgrO+eRcCAGEmq1Ozh5334OZUkrj2McYfXDRemNGImDIF4vVV59/5pxbr9er5cl2f7i/v9vsdpvNTkpeFMVsVr3/o/eKQrvJRm8Z0O5hAwDr9VqgQEoQKcZERIWWSumyaFygFKit2loV09AFlJeX13ntdzgcMEHbtrt9f3t7nSkTs9kMP70csxSGMTDGjuPonAvBAbD8YACA936aJqXUOI6LdtY0NVHa7/cPm7u6rp89e2bMiNEzxo0LBGiNR4C6KA+Hgy4AEQ+HQ3b50FpnZkCMkLHPm/sbLsTLl889gTEGKR0OByUlAChZ7Pf7fAcYY5eXl5vNpqqq7JXz6tWr+XzOOX/Y3M1ms8VizgEnM2ScH7nK7Qfn/AlYZYxNxh0OB/YY7ycefzgXMlUPEUdj8st6dXX1T/7J//np519aYp/8xV99e3v59s1V2y6bov3iF//ver1+8eLVs/OX89mqqpqyrLUqyprlkS5ftqc1925zdXd/f317s+87ZELVpQ9hv9+zGGKMVVUcdvuELCYMMZVlfVKqYRw/+/IXdw/b1dn5Rz/+REj1i8+/bnX98p01Ef3Zn361Ppn/o3/4N/6nf/y37XbofaiqKuPiy+UyD6McWUTGOXdm5JwjJsF5Rgz8aBAx5y6UZcmQG+MS4dBdEtF+v5+cWyzXJ6fPuS5jQsZJMh6ijz4E64L3gksi0mURYyyKKvMepdDOuf1+76LruoELpZR6+fJl8F4LjkCdtRmBqcqmKIpxnLL8f7u7zwW2KAr8k9e7DA4VSjnn9/v95eUlY+z58+d1XeevJL+eTzu9zKHEHBkhZSY+SgTGhBAizzezWZNS5JwjF21bcw5dN+bVi1IqJLKHA1DSUmFKtw83PBGLvpEynbzKSvNMvPDBZgGu4CrGuN/vx3E8PT3NMEQIoR+n+bwVQrRNRY8e1UgpMcxwnZQsE/DyLJzZ+VlrkqmfMca+72xMo+lfLF8WjQhSNgSMT//8D+7+zb/8t1e3X2w3/Xr5bHU6+8UXb6wT77x/Mu2765s7JtR6OZ/XBWfJp6TrZl7PiqIgCgIZZ+Ccs9bYyXx3dTlfnamqTghIUSmFTGy2B7u78xQpIfDssY0nq0XTNF//l6+/vX2bUny+Opuvz7qUzNif6frdl7UR6z/8/T9iiZqTs7/7X/3kt//qxz6xqiqqqso3P2Mdue493b3M83qS0nLERzMCY43PQHJVVYlhJJsHjK7rOXBE4gz6wRRFkSimlJTgXddRcIfDIaC2wyAY01XhYmRScODn63Nd1fvDA0BkiNc395dvr3VVXrx8vmoapRSXwhgzOat0WZUzzvm+32fSAoUgno4aIjSNbNuT5XJZVfxwsCGEcRy1llJK72N2RCCiuq5PTk5OT0/zEczEImfGQlfZG2kcR4I4DF0GtM7OzhaLBVHIpe2IJ0tRSqWlion+2f/yr//N//Wvpq77b/7mb33yV35ruVyuVovlcllVFReYgU/vIiJWVZWvASJkNucJQpb8CnHMjgCARNQPY/66yrLMpzDPagyPyWVCstwAeE8ASQRKGHMST0rgnGMwjuO4t8T1TJUsBLJmFNEMnbn86vq99z6ZjNvsDofDoSlkWZUQYt/3ArNVVeCcCwbee2etcfYICyMmOG4gE8R8gXVV5hysk5OTtq27/fZnP/vZdDCnp6fPnp+silnvgrdm1Zw8q1pnNlfdVdd1P3rnVbVa+hhiotxoPXUjKaX8rU5HqRDlJVlGiIdhyLcxgxJZSxRCMMaEEN577z2lRFHKum4YCs7Y/f3D5dV3wxheXjxbLBYxho0x++2mqiqhinGYOOfeuXE7HYYhQoIIV99dEZd1o+ZtlWvFy5cvdaWFZFnCmqkCXMk8JlprpdR4NFqH46mKPoxFcTT38UHxpix1SopzzP4NjMGzZ2fL5Xw+X+bOPbPL8g3LZPVxNIehv7m56fv+3XdfzebtSVlChLqui6LI1jtPdU2Vajx028NeSPnb/90/+K//7t8h718+O6fIc/nLJ34cR0oBADiTeQWax//8jjrnpFYxxmmatFSImI0ZkBJXMm9H8TGt7bi9BK61TumoKcyfByKerWe6lJUQEYlC7LqOwnb78BCYYroGHo1z1WQlTDqNsTtstveL+cIFstO0PewTxKppihJRcCYQk+DIGEcJKSUVKGan2SeWkHOOEsYYhVYxRq3LxXpVFMX19fX97bUQ4v333xdtwRmN4zgMI9eqLmS3u9tv3j6Y0hsrtCrLcrE6uXj1Uulyt9n2ff/k7v5Efs1nNM+sRVHkXjzG6ILP8HNKSakipbTf7w+Hw1dffbNctkKyvu/73Xh+fj5ftKvlyTs/WtVlxRjzwTZNW9W1FCLGWDYz049vv3sttHrx4qKZzw/bw7dfffuzz79q2+rFi5MXz57PmnlVVXVbScVSwEyuAwBPkUL06BEf42ORM0z/H+HAuCwjIW9DAAAAAElFTkSuQmCC\n"
          },
          "metadata": {},
          "execution_count": 73
        }
      ]
    }
  ]
}